Browse Topic: Automation

Items (3,418)

The Impact of Observability Constraints on the Planning for Employment of Robotic and Autonomous Systems

2026-01-7514

9/22/2026

Employment of Robotic and Autonomous Systems requires a different paradigm of mission planning. The GTRI Missioneer for Organic Collaborative Kill-Chains (MOCKS) effort was developed to mature the concepts of mission planning in light of autonomy, where the decision making is distributed across the battlespace and each individual entity has limited awareness of global state. The paper presents some initial characterizations of the impact of constraints on periods out of communication, or no-comms windows, on the number of resources required for missions of a certain operational area. This metric, along with the foundational metric of remaining effective range margin are foundational to robust a priori planning.

Spratley, Michael

Cooperative Object Tracking for Improved World Modeling in Multi-Agent Systems

2026-01-7516

9/22/2026

This paper presents a cooperative object tracking framework that enables robots to share object observations, improving world model accuracy and consistency in environments with occlusions. An open-source, MHT-based object tracking package was applied in conjunction with an inter-robot communication system developed to fuse object observations across multiple robots. Experimental results demonstrate greater than 1.4-fold improvements in tracking performance in cluttered, occluded environments compared to individual tracking.

Kennedy, William, Alton, Nicholas

An Assessment of Biomanufacturing in Forward Deployed Locations

2026-01-7557

9/22/2026

Biomanufacturing uses microorganisms to produce chemicals or materials of interest, much like a brewery uses fermentation by yeast to produce the alcohol in beer. Biomanufacturing relies upon synthetic biology to reprogram yeast or other microorganisms to produce something of greater value, such as fuel, food, or pharmaceuticals. Industrial biomanufacturing has made significant advances and the products it can deliver include reactive coatings and textiles, sensors, optical materials that can bend light, and new therapeutics such as antimicrobials and vaccines. The convergence of synthetic biology, robotics, and artificial intelligence is opening the way to produce materials never before possible in the commercial market. These same technologies create the opportunity for the miniaturization of this technology to fit into ever more compact spaces, bringing forward deployment of these mini-factories closer and closer to the point of need.

Ahern, Brooke, Crumbley, Annie, Walker, Anne, Grodecki, Joseph

Hybridnav: A Hybrid Approach to Zero-Shot Object Detection with Adaptive Exploration for Autonomous Reconnaissance

2026-01-7517

9/22/2026

Autonomous reconnaissance in unknown or contested environments demands robust perception systems capable of identifying diverse objects without prior training data. This paper presents HybridNAV, a hybrid framework that combines multiple foundation models with an adaptive navigation system for zero-shot object detection and autonomous exploration. Unlike monolithic detection models, HybridNAV’s multi-model fusion achieves balanced precision (0.60) and recall (0.58) with a macro F-score of 0.59, representing a 24% improvement over single-model baselines. The adaptive navigation system reduces scan time by 25% and path length by 30% compared to static waypoint approaches, while operating in real-time at 3.2 Hz with sub-100 msec latency on resource-constrained hardware. All processing is performed locally on the robotic platform, eliminating reliance on external communication infrastructure—a critical requirement for operations in communication-denied environments. We evaluate HybridNAV in both simulated indoor scenes and physical robot trials, demonstrating its effectiveness for intelligence gathering in unknown environments.

Indurthi, Hemanth, Martinson, Eric

Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles

J3016_202609 (Current)

9/20/2026

This document describes [motor] vehicle driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis. It provides a taxonomy with detailed definitions for levels of driving automation, ranging from no driving automation (Level 0) to automated driving under all conditions in which humans can drive, with human driving not needed (Level 5), in the context of [motor] vehicles (hereafter also referred to as “vehicle” or “vehicles”) and their operation on roadways: Level 0: No driving automation Level 1: Driver support for steering OR speed, with continual driver supervision necessary and driver intervention when needed Level 2: Driver support for steering AND speed, with continual driver supervision necessary and driver intervention when needed Level 3: Automated driving under defined conditions, with human driving needed following an alert or evident vehicle malfunction Level 4: Automated driving under defined conditions, with human driving not needed to mitigate risk Level 5: Automated driving under all conditions in which humans can drive, with human driving not needed. The simple level descriptors have been changed to improve understanding of the differences among levels, but these are NOT the definitions of the levels of driving automation. See the definitions of each automation level in Sections 4 and 5 for explanation of these changes. These level definitions, along with additional supporting terms and definitions provided herein, can be used to describe the full range of driving automation features equipped on [motor] vehicles in a functionally consistent and coherent manner. “On-road” refers to publicly accessible roadways (including parking areas and private campuses that permit public access) that collectively serve all road users, including cyclists, pedestrians, and users of vehicles with and without driving automation features. The levels apply to the driving automation feature(s) that are engaged in any given instance of on-road operation of an equipped vehicle. As such, although a given vehicle may be equipped with a driving automation system that is capable of delivering multiple driving automation features that perform at different levels, the level of driving automation exhibited in any given instance is determined by the feature(s) that are engaged. This document also refers to three primary actors in driving: the (human) user, the driving automation system, and other vehicle systems and components. These other vehicle systems and components (or the vehicle in general terms) do not include the driving automation system in this model, even though as a practical matter a driving automation system may actually share hardware and software components with other vehicle systems, such as a processing module(s) or operating code. The levels of driving automation are defined by reference to the specific role played by each of the three primary actors in performance of the DDT and/or DDT fallback. “Role” in this context refers to the expected role of a given primary actor, based on the design of the driving automation system in question and not necessarily to the actual performance of a given primary actor. For example, a driver who fails to monitor the roadway during engagement of a Level 1 adaptive cruise control (ACC) system still has the role of driver, even while they are neglecting it. Active safety systems, such as electronic stability control (ESC) and automatic emergency braking (AEB), and certain types of driver assistance systems, such as lane keeping assistance (LKA), are excluded from the scope of this driving automation taxonomy because they do not perform part or all of the DDT on a sustained basis, but rather provide momentary intervention during potentially hazardous situations. Due to the momentary nature of the actions of active safety systems, their intervention does not change or eliminate the role of the driver in performing part or all of the DDT, and thus are not considered to be driving automation, even though they perform automated functions. In addition, systems that inform, alert, or warn the driver about hazards in the driving environment are also outside the scope of this driving automation taxonomy, as they neither automate part or all of the DDT, nor change the driver’s role in performance of the DDT (see 8.13). It should be noted, however, that crash avoidance features, including intervention-type active safety systems, may be included in vehicles equipped with driving automation systems at any level. For automated driving system (ADS) features (i.e., Levels 3 to 5) that perform the entire DDT, crash mitigation and avoidance capability is part of ADS functionality (see also 8.13). Note that this document provides a taxonomy and definitions and is not a safety standard. The document is not intended to provide guidance for safe vehicle operation by the driving automation system.

On-Road Automated Driving (ORAD) Committee

Design and Research of Large-Tire Replacement Robots

2026-99-1127

9/11/2026

In view of the large volume and weight of the tires of mining dump trucks and the difficulty in replacing them, a large tire replacement robot is proposed based on the tire parameters and the tire replacement process. The overall research scheme for the robot was developed using the functional analysis method, and the functional element solution and combination were completed. Based on the best solution obtained, a three-dimensional model of the tire changing robot was established using the SolidWorks software, followed by control system design and workflow analysis. To investigate the robot's operational kinematics, a simulation was conducted in the SolidWorks Motion module. The motion curve of the flipping platform during its operational state was obtained. A finite element simulation of the robot's front support beam was performed using ANSYS Workbench to obtain its stress and deformation contours under both no-load and heavy-load conditions. The structural parameters of the front support beam were optimized, focusing on its mechanical characteristics under heavy-load conditions, and the response surfaces of different parameters were obtained. The optimization yielded a 9.599 kg reduction in the mass of the front support beam. The maximum stress of the grasping mechanism under static simulation analysis is 50.617 MPa, with the maximum deformation of 0.4221 mm occurring at the end of the mechanical hand. Ground contact simulation for the robot's walking tires was conducted with Abaqus. Employing the Mooney-Rivlin hyperelastic model, this study investigated the mechanical response of the tire to static and dynamic loading, leading to the identification of the optimal operational load. The simulation results show that there is no interference among the various mechanisms of the large tire changing robot during operation. It can quickly complete the tire installation and removal tasks with precise control, and its strength and rigidity meet the requirements. This verifies the rationality and feasibility of the robot. The research on the large tire changing robot can provide a new approach for the maintenance of large transport vehicles such as mining dump trucks.

Tian, Liyong, Zhang, Haijian

Reliability Evaluation of Transmission Accuracy for RV Reducers Based on Uncertainty Theory

2026-99-1101

9/11/2026

In reliability evaluation of RV reducers using accelerated degradation tests, practical constraints (e.g., test costs and resource shortages) often lead to insufficient test iterations or small sample volumes. This results in limited insights into the product’s overall degradation trajectory, inadequate data for reliability analysis, and notable epistemic uncertainty. Conventional accelerated degradation models—rooted in probability theory—depend on the large numbers, rendering them ill-suited to address such uncertainty in small-sample scenarios. Uncertainty theory, a modern mathematical framework developed to characterize epistemic uncertainty, has garnered broad academic interest for its strong adaptability to small-sample contexts. Accordingly, this study explores the evaluation of RV reducer reliability using accelerated degradation data and uncertainty theory, aiming to mitigate epistemic uncertainty arising from small sample sizes. Specifically, this work develops a transmission accuracy degradation model for RV reducers based on the Liu process—a core component of uncertainty theory—that incorporates both inter-sample individual variability and the epistemic uncertainty inherent in the degradation process. This study also assesses the reducer’s reliability and service life; comparative analysis against probability-theoretic models confirms the proposed model’s advantages in small-sample scenarios.

Luo, Min, Huang, Jinxing, Dai, Jinzhen, Shu, Ke

Optimization of Order Picking in an AMR-Assisted Picker-to-Parts System

2026-99-1567

9/11/2026

With global retail sales expanding and same-day delivery demand on the rise, efficient order picking operations in warehouses have become critical to success. To improve order picking processes, warehouse managers increasingly rely on autonomous mobile robots (AMRs), which improve the performance of traditional picker-to-parts systems. This paper investigates an AMR-assisted picker-to-parts system in which a set of customer orders must be fulfilled. The orders are first batched, and the resulting batches are assigned to individual pickers. Each picker works in a batch-by-batch manner, manually retrieving items from picking aisles and handing over the completed batch to an AMR waiting at the cross aisle. After receiving a full batch, the AMR transports it to the designated depot before returning to serve the next batch. The objective is the minimization of the total tardiness of all orders. The problem is formulated as a mixed-integer programming (MIP) model, and several effective heuristic algorithms are developed. Extensive computational experiments are conducted to evaluate the performance of the proposed algorithms and compare them with a commercial MIP solver.

Jin, Bo, Peng, Jianxin

New Nonlinear Buckling Solutions of Piezoelectric Truncated Conical Shells

2026-99-1262

9/4/2026

Piezoelectric materials are highly valued in engineering for their electromechanical coupling. With these characteristics, structural applications utilizing such materials are increasingly being employed across a variety of disciplines. Among these structural configurations, piezoelectric conical shells have garnered significant interest owing to their inherent electromechanical coupling behavior, making them ideal for applications in various devices such as actuation systems, sensing mechanisms and energy harvesting solutions. To ensure the structural safety of these devices, assessing the stability of such shell structures is essential. This study conducts an analysis of the buckling stability of truncated piezoelectric conical shells. To this end, a theoretical buckling model for piezoelectric truncated conical shells is established, based on first-order shear deformation theory combined with nonlinear pre-buckling deformations. Utilizing a novel set of displacement trial functions within the Galerkin framework, this study derives precise critical buckling loads along with their associated mode shapes. The accuracy of the model is verified through comparative studies in the numerical section. Subsequently, the influence of key parameters—including applied voltages, semi-apex angles, and shell thickness—on the buckling behavior is investigated. The findings indicate that including the nonlinear pre-buckling deformation in the analysis is essential for ensuring reliable predictions. This research offers a theoretical foundation for the dependable design and assessment of piezoelectric truncated conical shells. Moreover, they also create opportunities for smart structures in aerospace, civil, and robotics, where accurate predictions of stability under electromechanical loading are critical.

Zhang, Junlin, Chen, Lide, Jia, Jufang, Zhou, Zhenhuan

Assembly Accuracy Optimization of Aero-engine Section Based on Dynamic Weighting Multi-Objective Optimization Algorithm

2026-99-1272

9/4/2026

The pose-solving method for aero-engine component docking assembly often faces challenges such as slow convergence and susceptibility to local optima when dealing with complex optimization problems involving multiple features and constraints. This paper proposes an optimized assembly pose solution method for engine sections based on an improved multi-objective optimization algorithm. The method first preprocesses the high-density point clouds obtained from 3D scanning to extract geometry such as feature points, lines, and surfaces. It builds an assembly constraint model with geometric relations and process needs. It focuses on the pose solution phase: we transform the assembly problem into a nonlinear optimization problem to minimize parallelism error, gap error, and step error. In order to solve this multi-objective problem efficiently, we propose an iterative multi- objective optimization algorithm as the optimization engine and propose a dynamic weight allocation strategy. During iteration, the strategy adaptively adjusts the weight coefficients of three error terms in the overall fitness function due to the evolution of the population and convergence of each error term, guiding the search direction and balancing the algorithm's global exploration and local exploitation ability. Our results show that instead of adopting an optimization algorithm with fixed weights and a multi-Objective optimization system with fixed weight, the proposed pose solution method based on dynamic weight multi- objective optimization algorithm achieves a high accuracy and stability of the solution and can easily and accurately produce a good pose matrix which meets challenging assembly constraints, providing a practical theoretical framework and technical support for achieving high-quality automated engine assembly.

Huang, Mi, Wu, Guanghui, Su, Xun, Xu, Yongqian, Ding, Han, Liu, Xiaopeng

Adaptive-Weighted Coupling-Aware Gaussian Processes for AFP

2026-99-1277

9/4/2026

Composite materials have gained widespread application in the aerospace field due to their advantages, such as high specific strength, high specific modulus, and corrosion resistance. Automated placement technology, as an emerging automated manufacturing method, is gradually replacing traditional manual placement processes and demonstrating significant advantages in composite manufacturing. Currently, the automated placement process for composite materials faces challenges such as insufficient experimental samples and strong coupling relationships between process parameters, leading to low fitting accuracy in process parameter optimization models. To address this, this paper proposes a placement process parameter optimization method based on model weight adaptive allocation. This method integrates three key technologies: a coupling-aware Gaussian process based on combined kernel functions, a weight allocation ensemble model based on leave-one-out cross-validation, and a multi-criteria adaptive sampling mechanism. Experimental validation demonstrates that the integrated model achieves a coefficient of determination R^2 = 0.82, which represents a superior fit compared to the R^2 = 0.65 achieved by a single-kernel Gaussian model and the 0.76 obtained from a single sampling. Furthermore, both the Root Mean Square Error (RMSE=0.92) and Mean Absolute Error (MAE=0.70) are lower than those of traditional baseline models. This framework provides an effective solution for optimizing parameters in the automated placement process for composite materials.

Zuo, Rui, Du, Tingting, Lv, Ruiqiang

Design and Validation of a 7-DoF Robotic Arm Featuring Hybrid Pneumatic-Electric Actuation

2026-99-1222

9/4/2026

To enable more natural motion mapping between the human arm and a robotic counterpart while reducing control complexity, this paper presents a novel seven-degree-of-freedom (7-DoF) bionic robotic arm with hybrid pneumatic–electric actuation in an antagonistic configuration inspired by the skeletal structure and muscular actuation of the human upper limb. The design combines the high power density and intrinsic compliance of pneumatic artificial muscles with the precision and stability of electric motors, improving motion adaptability and payload-to-weight performance. Kinematic feasibility and motion smoothness for human-like waving are validated via forward kinematics and redundancy-resolved inverse kinematics, together with trajectory simulations. To quantitatively evaluate dexterity and operational range, Monte Carlo sampling is used to generate reachable postures across the workspace, producing a wrist activity map that characterizes attainable orientations and maneuverability. A prototype testbed is built to verify physical performance. Joint-angle tracking experiments for the wrist and elbow, as well as whole-arm coordinated-motion tests, demonstrate accurate trajectory tracking, smooth transitions, and stable motion. These results confirm the mechanical soundness and effectiveness of the proposed hybrid antagonistic actuation scheme. This work provides a practical basis for advanced control development and offers insights into hybrid actuation design for bionic robotic systems.

Dai, Yuanquan, Guo, Zhiqin, Zi, Mingkang, He, Zhaoyang, Song, Yongwei, Xie, Yinhui, Li, Jun

Automotive Engineering: September 2026

26AUTP099/3/2026

Bespoke at scale: How generative AI is rewriting the economics of manufacturing automation The economic logic behind factory software upgrades is breaking down. Navigating an increasingly complex engine oil landscape As the impending ILSAC GF-8, dexos 1 Gen 4, and a hybrid specification continue to obscure the North American landscape, passenger car engine oils need additive solutions that can help simplify blending operations and optimize product portfolios. High-temperature joint reliability Why preload retention matters more than fastener grade. Designing out corrosion at the wheel The case for advanced powder coatings. Editorial Where to? The challenges of automated driving around the world The Navigator Is China really our biggest automotive security threat? Better safety through collaboration at Toyota research center ATS 2026: automated driving is changing The software-defined technician: Manufacturing's next human capital revolution Aumovio says system can BAC with non-invasive finger touch How conveyors have carved a role in mastering manufacturing 2027 Mercedes-Benz S-Class: Same as ever, which is very good 2026 Lucid Gravity: Highly efficient luxury hauler Product Briefs Spotlight: Adhesives and coatings; sustainable materials Q&A How an automotive startup uses and doesn't use customer data

The software-defined technician: Manufacturing's next human capital revolution

26AUTP09_09

9/1/2026

For the past several years, manufacturing leaders have obsessed over a single question: How do we capture the knowledge of our retiring experts before they walk out the door for the last time? The answers have poured in, from digital work instructions and video libraries to AI-assisted knowledge bases and immersive training simulations. Billions of dollars have been deployed to bottle the expertise of master machinists and senior quality inspectors who spent decades developing an almost intuitive ability to detect a hairline fracture, sense when a tolerance is drifting, or feel when a machine is running wrong. That work was necessary. But it was also, in a sense, the easier problem. The harder question is only now coming into focus: once that knowledge is digitized, what exactly do the remaining specialists do?

Panigrahi, Dijam

ATS 2026: automated driving is changing

26AUTP09_08

9/1/2026

Despite a distinct lack of superheroes, the automated driving community scored big victories in San Diego at the end of July. The annual Automated Transportation Symposium opened just as the massive pop culture event that is ComicCon was leaving town. Iron Man and Aang stared out from nearby billboards as the conference tackled announcements regarding Zoox, changing automated vehicle regulations, and repeated discussions on how AVs need to improve interactions with first responders.

Blanco, Sebastian

BESPOKE AT SCALE: how generative AI is rewriting the economics of manufacturing automation

26AUTP09_01

9/1/2026

The economic logic behind factory software upgrades is breaking down. For the past four decades, automating a factory has meant one thing: buying into a large industrial software platform. Manufacturers turned to established suppliers such as Rockwell Automation and Siemens for the control systems, execution layers, and quality software that run their plants, millions of lines of rigorously engineered code, developed under strict standards and wrapped in guardrails. That rigor was never optional. When software commands a robot arm, a stamping press, or a paint line, a defect is not a bug ticket; it is a safety incident. The engineering discipline behind these platforms reflects that reality, and has served the industry well. But discipline at that scale comes at a price. Platform deployments are measured in millions of dollars and years of integration work, which means they only make economic sense for the largest, most repeatable problems a plant faces. Everything else, the hundreds of smaller, plant-specific pain points that erode margins every day, has largely gone unaddressed. Running a modern factory became expensive by design.

Cros, Fabien

2026 Lucid Gravity: Highly efficient luxury hauler

26AUTP09_13

9/1/2026

I'm not sure what to do with my hands. This is my typical response to any vehicle outfitted with a hands-free, eyes-on driver's assistance feature. After a few moments of the feature being enabled, I usually place my hands back on the steering wheel even though the vehicle is navigating the road ahead via an elaborate system of sensors and computers. The Lucid Gravity gets the same treatment. Still, it's handling the roadway deftly, without my input but definitely with my full attention. The second vehicle from automotive startup Lucid is a three-row SUV that more resembles a large station wagon or stylish minivan than the tall, upright sport utility vehicles that have overwhelmed the nation's roads. It's sleek, quick, modern, and filled with the latest technology. More importantly, it's enjoyable from behind the wheel with enough cargo space for even the most daring and bank-busting trip to Costco.

Baldwin, Roberto

A New Research Facility for Robotics and Alloy Discovery in Texas

26AERP09_09

9/1/2026

Researchers have received a $24.9 million grant to develop an NSF Materials Innovation Platform where universities, national laboratories and industry members can run alloy-discovery campaigns using robotic systems and artificial intelligence. Texas A&M University, College Station, Texas A six-year, $24.9 million grant from the U.S. National Science Foundation (NSF) will establish the Autonomous Robotic Metallurgist Materials Innovation Platform (ARM-MIP) at Texas A&M University - a national user facility where robots and artificial intelligence take on the repetitive labor of alloy discovery, freeing scientists to focus on discovery itself. ARM-MIP will be sited at The Texas A&M University System RELLIS Campus in Bryan, a dedicated research campus that also hosts the Texas A&M Engineering Experiment Station and the U.S. Army Transformation and Training Command's central testing hub at the George H.W. Bush Combat Development Complex. The platform is designed to reach more than 200 users a year and 50 alloys per month in its first year, scaling to more than 200 alloys per month by year six.

AVSC Best Practice for ADS Remote Assistance Training and Human Factors

AVSC-I-07-20268/25/2026

AVSC Best Practice for ADS Remote Assistance Training and Human Factors is intended to support the development of processes regarding automated driving system-dedicated vehicle (ADS-DV) remote assistant training, qualification, assessment, and performance-related human factors. It provides information to standardize communication about remote assistance (RA) programs to stakeholders to increase public trust in the operation of ADS-DVs by providing guidance on training for remote assistants.

Automated Vehicle Safety Consortium

Design of a Digital Twin for Robot-Assembled Workpiece Transfer Station and Virtual Commissioning with It

2026-99-0347

8/14/2026

In this research, the design of a digital twin system for a Robot-Assembled Workpiece Transfer Station (RAWTS) and virtual commissioning with it were detailed, aiming for debugging high-repeatability, high-precision robotic motions. The system employs a structured three-layer digital twin framework, Physical, Digital, and Information Fusion layers, interconnected via an OPC UA communication architecture to enable real-time virtual-physical data synchronization. The 6-axis industrial robot’s kinematic model is established using the D-H parameter method, and the translational end-effector’s kinematic relationships are configured with defined OPEN/CLOSE poses. A behavior-driven digital twin model is constructed within NX MCD, incorporating lightweight-processed 3D geometry from SolidWorks. Virtual commissioning involves PLC and robot program integration, OPC UA-based signal mapping, and kinematic path planning with reachability validation to avoid singularities and collisions. Key joint angles at critical path points are optimized, and virtual-physical integration debugging is performed, resulting in first-attempt success in physical operation. The study demonstrates that the NX MCD-based digital twin approach effectively validates control logic, optimizes robot trajectories, reduces on-site debugging time, and enhances operational precision and safety, offering a practical reference for digital twin applications in robotic systems.

Zang, Yuping, Wang, Ye, Fu, Hudai, Li, Weiwei, Jiang, Zhiyu, Wang, Dayu

Structural Design and Mechanical Performance Analysis of Key Components of Deicing Robots for Transmission Lines

2026-99-0346

8/14/2026

Extreme winter weather often leads to ice accretion on transmission lines. Manual removal is inefficient, costly, and poses safety risks. To address this issue, this paper presents the design of a de-icing robot to replace manual operations for transmission line de-icing. The main content focuses on the detailed structural design of the robot, including the mobile platform, de-icing mechanism, and adaptive adjustment module. Finite element simulations are conducted on key components to verify the structural rationality and the correctness of material selection. The proposed de-icing robot enhances the safety of the de-icing process, improves operational efficiency, and provides a valuable reference for transmission line de-icing methods, demonstrating significant practical value.

Chang, Hao, Zhen, Chen, Han, Fengmei, Li, Cheng

Mechanical Structure Design and Dynamics Simulation of an Exoskeleton Leg Rehabilitation Robot

2026-99-0902

8/7/2026

In response to the challenges of training and rehabilitation for patients with leg dysfunction, this research focuses on two core requirements: “bionic adaptation” and “safety assistance”. It introduces a novel exoskeleton leg rehabilitation robot designed to support diverse rehabilitation exercises for individuals with leg disabilities during therapy. The robot system consists of a lumbar support structure, thigh mechanical components, calf mechanical components, leg fixation straps, and foot mechanical structures, and achieves multi degree of freedom motion simulation through three main joints: hip joint, knee joint, and ankle joint. Each mechanical leg has three independent degrees of freedom, which can effectively simulate the natural movements of the human lower limb, such as flexion, extension, abduction, etc., during the gait cycle, thus meeting the functional needs of patients for different movement modes during rehabilitation training. On the basis of structural design, this study further utilizes multi-body dynamics simulation software ADAMS to conduct kinematic and dynamic analysis of the exoskeleton robot. By simulating the joint torque of the exoskeleton legs under ideal working conditions, the rationality and smoothness of the mechanism design are verified. The simulation results not only reflect the performance of the robot in typical rehabilitation actions, but also provide a theoretical basis and data support for the selection and parameter matching of key execution components (such as servo motors, reducers, etc.), laying an important foundation for the physical development and control strategy optimization of the robot system.

Mu, Xiaoqi, Ma, Chao, Li, Weijie, Pu, Shuai, Liu, Jiaqi, Wang, Ruiyin, Zhang, Xiaodong

2026 Toyota RAV4 just the first to benefit from Arene and Toyota's WOVEN CITY

26AUTP08_01

8/1/2026

A dispatch from the automaker's “let's just try it” city finds hydrogen fuel cells, automated parking robots, and a robust spirit of innovation. For a planned high-tech community created by an automaker, Woven City is not laser-focused on automobiles and transportation. In fact, to get a glimpse of Toyota's priorities here, look to the pedestrian stoplights at intersections. They remain a constant green, until the connected city senses an approaching vehicle and turns them red. This focus on pedestrians over vehicles is one small part of Toyota's rebranding as a mobility company. Toyota announced Woven City at CES 2020, converting its recently closed Higashi-Fuji factory, which built over 7.5 million Toyota vehicles during a 53-year run, into a blank slate for new technologies, automotive and otherwise.

Blanco, Sebastian

Stewart Platform Position and Attitude Error Compensation Based on Improved Particle Swarm Optimization

2026-99-0104

7/31/2026

The six-degree-of-freedom Stewart platform, as a high-precision parallel robot, is widely used in fields such as aerospace and precision manufacturing. However, its complex structure and diverse sources of error (such as manufacturing errors, assembly errors, rod deformation, etc.) make it difficult to effectively control position and attitude errors. This article proposes a Stewart platform position and attitude error compensation method, relying on the improved particle swarm optimization algorithm. By establishing a position and attitude error model for the platform and optimizing the driving joint error using the IPSO optimization, the position and attitude error of the platform have been significantly reduced, providing a new solution for error compensation of high-precision parallel robots.

Zhu, Ming, Wang, Baichao

Study on the Adaptability of Underwater Propeller-Driven Bernoulli Adsorption Device on Irregular Walls

2026-99-0172

7/31/2026

The propeller-driven Bernoulli adsorption device (PBD) has both propulsion and adsorption functions, being suitable for dual-mode underwater robots. Currently, there have been studies on the adsorption performance of PBD on the flat surface. However, the surface morphology of underwater engineering structures is different, and PBD’s adsorption performance on irregular walls still remains unknown. In this letter, based on the potential application scenarios of underwater dual-mode robots, we established four types of irregular wall models to investigate PBD’s adsorption performance on irregular walls. Through CFD simulations and experiments, the adsorption state was analyzed, and the adsorption performance was quantitatively studied.

Liu, Siyue, Hua, Zhong, Yang, Canjun

Docking Methodology for Large-Sized Irregular Castings via Industrial Robot Manipulation

2026-99-0170

7/31/2026

Large-sized irregular castings are critical components extensively employed in large-scale equipment manufacturing. Due to their substantial dimensions and complex geometries, the assembly and docking processes between different components present significant challenges. To address the docking problem between large-scale irregular castings, this study proposes a casting docking method based on relative pose, along with a modeling approach for irregular castings, and accomplishes the docking process through the control of an industrial robot. Firstly, the current poses of feature points on the docking surfaces are measured. Based on these measurements, the relative pose transformation relationship between the center point of the docking surface and the robot’s Tool Center Point (TCP) is established, thereby constructing the docking model. This model calculates the relative deviation between the current pose and the theoretical pose. Subsequently, the robot motion is controlled according to this deviation to achieve precise docking. Finally, a simulation environment was built using KUKA. Sim Pro with Office Lite to simulate the docking process of large-sized irregular castings. The results demonstrate that the relative pose-based docking method effectively accomplishes the docking task. This study provides an effective solution for the docking of large-sized irregular castings.

Liu, Haoran, Jia, Haili, Wang, Aimin, Xigang, Fan, Peidong, Su

Parameter Identification for the Dynamics Model of a Robotic Grasping Process Based on SFOA

2026-99-0123

7/31/2026

To precisely simulate the nonlinear dynamic characteristics of a robotic arm grasping cylindrical objects from storage units, this study establishes a dynamic model of the robotic grasping process incorporating Coulomb and viscous friction models to characterize frictional properties. Furthermore, to effectively identify unknown parameters in the dynamic model, a parameter identification method based on the Superb Fairy-wren Optimization Algorithm (SFOA) is proposed. The root-mean-square error (RMSE) between the displacement responses from the dynamic model and the experimentally acquired displacement data serves as the optimization objective. Multiple sets of experimental data are utilized to identify the unknown parameters of the dynamic model. The results demonstrate that when the identified parameters are applied to the dynamic model, the goodness-of-fit between the model’s response displacement data and the experimental displacement data exceeds 0.999. This validates the effectiveness and accuracy of the proposed method for identifying unknown parameters in dynamic models.

Shen, Shaofeng, Yang, Liu, Wang, Zihan, Han, Qunyi

Analysis and Verification of the Stiffness of Flexible Mechanisms

2026-99-0103

7/31/2026

Recent advances in precision motion technology have heightened the requirement for precise stiffness analysis in flexible mechanisms. This paper begins with a theoretical analysis, constructing a mathematical expression for the stiffness of flexible mechanisms, providing a systematic framework for analysis. Subsequently, the study employed finite element analysis on both single and double parallelogram flexible mechanisms to validate the proposed theoretical stiffness formulas. This process not only confirmed the effectiveness of the proposed expressions but also highlighted the influence of different structures on stiffness characteristics. The finite element analysis results validate the proposed theoretical model as an effective and reliable tool for predicting the stiffness of flexible mechanisms. By establishing a reliable predictive model, this research paves the way for the informed design and systematic optimization of next-generation flexible mechanisms in precision motion engineering.

Cai, Dongchen

Design and Research of Robotic Arm for Belt Conveyor Roller Replacement

2026-99-0187

7/31/2026

To address the high failure rate of rollers in coal mine belt conveyors, the inefficiency of manual replacement, and the operational disruptions caused by maintenance shutdowns, this study proposes a robotic arm system capable of replacing rollers without halting conveyor operations. The research focuses on the kinematic performance and path planning strategy of the robotic arm. A kinematic model is established using the Denavit–Hartenberg (DH) parameters, and the workspace distribution is analyzed via the Monte Carlo method. The results show that the horizontal reach exceeds 2020 mm and the vertical reach extends up to 2000 mm, which fully satisfies the spatial requirements for roller replacement across the entire conveyor system. In the path planning phase, an obstacle expansion model is constructed, and an improved Informed RRT* algorithm is implemented to generate collision-free trajectories, ensuring effective obstacle avoidance. To improve trajectory smoothness, path pruning and cubic B-spline interpolation are applied to refine the initial paths. For trajectory planning in joint space, quintic polynomial interpolation is employed, with boundary conditions set to ensure zero velocity and zero acceleration at both the start and end points, thereby guaranteeing smooth and stable motion of the robotic arm. Simulation results indicate that joint angles, angular velocities, and angular accelerations vary smoothly throughout the roller grasping process, without abrupt changes, and converge to zero at the beginning and end of the trajectory. End-effector trajectory tracking error analysis reveals positioning errors within 0.8 mm for side rollers and 3 mm for central rollers, well within acceptable engineering accuracy thresholds. This work provides a theoretical foundation and a practical implementation framework for advancing automation and intelligent operation in roller replacement tasks within coal mine belt conveyor systems.

Pu, Congyuan, Qian, Ke

Design and Control of a Target Plate Fastener Assembly and Disassembly Actuator for Divertor Maintenance in Fusion Reactors

2026-99-0182

7/31/2026

With the development of controlled nuclear fusion technology, the tokamak device, as the most promising magnetic confinement fusion reactor for advanced engineering applications, requires remote maintenance of its internal components, which has become a key factor affecting both operational efficiency and safety. As a critical component directly exposed to high-temperature plasma, the divertor target plate needs to be periodically replaced and carefully maintained to ensure stable and reliable reactor operation. However, this region is subject to extreme conditions, including high temperature, high vacuum, and intense radiation, making conventional manual maintenance infeasible. This necessitates the development of intelligent and automated teleoperation systems. To address the automated assembly and disassembly requirements of divertor target plates, this study designs an integrated target plate actuator comprising key functional units: a positioning module, a screwing module, a quick-change module, and a passive compliance structure. The actuator achieves rapid and precise alignment with target plate holes, accommodates bolts of different specifications, and exhibits excellent impact resistance. Furthermore, stiffness and mechanical analyses, supported by finite element simulations, verify the actuator’s safety and reliability under high loads and impact forces. To further enhance operational performance, a segmented disassembly and assembly control strategy based on reinforcement learning is proposed, enabling the actuator to adaptively handle torque variations and ensure precise and stable bolt operations. The results demonstrate that the proposed actuator and control strategy significantly improve the accuracy, stability, and efficiency of target plate operations under complex working conditions, providing a reliable solution for automated divertor maintenance in tokamak devices.

Zang, Xizhe, Yu, Xingzu, Cao, Zhangbin

Robotic Grinding Trajectory Planning and Correction Method for Large-Scale Complex-Shaped Products

2026-99-0227

7/31/2026

Due to the inherent characteristics of large dimensions, complex curved surfaces, and densely distributed protrusions present in aerospace products, conventional offline programming and trajectory planning techniques for robots primarily prioritize the facilitation of uninterrupted grinding processes and the generation of points along trajectories on surfaces characterized by smoothness. However, these methods encounter challenges in identifying and proactively avoiding surface protrusions during the planning phase. The present paper puts forth a proposal for an automated robot trajectory planning method for grinding operations. This method is predicated on the integration of region partitioning and deformation correction. Specifically, this method first identifies protrusions based on curvature features and rule matching, followed by an analysis of the feasible workspace of a six-axis industrial robot equipped with an external axis. The product surface is discretized into multiple regional units according to the distribution characteristics of protrusions and the constraints of the feasible workspace. Subsequently, a parameter-optimized parallel sectioning method is employed to independently plan trajectories for each unit. The utilization of on-site measured point cloud data facilitates the analysis of contour deviations. In addition, grinding trajectories are dynamically corrected to meet high-precision process requirements. This approach effectively overcomes the challenge that trajectory planning for large-scale, complex-shaped products is easily affected by protrusions. According to the established methodology, the development of an offline programming software system for robotic automatic grinding was initiated. To this end, experiments were conducted on aircraft wall panels to plan and modify grinding trajectories using the proposed method. This process was undertaken to validate the effectiveness and engineering practicability of the proposed method.

Fan, Changhao, Wang, Mingyang, Lv, Ruiqiang, Zhou, Peng

Design Modeling and Simulation Analysis of a Stiffness Enhanced Soft Pneu-Net Actuator

2026-99-0855

7/30/2026

Pneumatic soft actuators are widely used in soft robotic systems because of their inherent compliance and smooth deformation. However, their practical application is often limited by low structural stiffness, restricted load-bearing capability, and insufficient tip output force. These limitations become more pronounced in tasks that require stable force transmission or precise interaction with the environment. In response to these limitations, this study proposes a stiffness-enhanced pneumatic soft actuator based on a modified multilayer structural configuration. The actuator integrates chamber layers, a constraint layer, and periodically distributed rigid reinforcement elements. This structural arrangement improves the way internal pressure is converted into bending deformation and external force output, while avoiding excessive local expansion of the chambers. Based on this actuator, a coupled theoretical model is developed to describe the relationship between internal pressure, bending angle, and tip force. The model considers both the hyperelastic behavior of the silicone material and the geometric constraints introduced by chamber deformation. Finite element simulations are performed to examine the actuator’s mechanical response under different pressure inputs. This effect becomes evident at higher pressure levels. Both free-bending behavior and tip contact force generation are analyzed. The simulation results follow the same trends as the theoretical predictions, and the overall deviation remains below 10% across the investigated pressure range. The agreement shows that the model reflects the main mechanical response. Compared with a conventional pneumatic soft actuator, the proposed design achieves higher stiffness and larger tip output force, while maintaining compliant motion and smooth bending behavior. The actuator structure and model may serve as a useful basis for pneumatic actuator design in force-demanding tasks.

Zhou, Wenjing, Ma, Rui, Lu, Mingyue, Wu, Yanyan

Design and Experiment of a Stable Seed Supply Control System for an Elevating Type Sugarcane Seed Supply Device

2026-99-0819

7/30/2026

Aiming at the problems of seed cane pile-up and unstable seed supply efficiency in the sugarcane seed production line caused by the seed supply device, a stable seed supply control system was designed, which consists of a seed collection box, an elastic seed-clearing plate and an electrical control system, etc. The EDEM-RecurDyn coupling simulation was adopted to analyze the seed supply process, and the optimal elastic seed-clearing plate structure was designed. Using the single factor test and Box–Behnken experimental design analyzed the effects of the seed supply belt speed, the speed of the first conveyor belt, the number of sugarcane seeds in the collection box and the seed cutting efficiency on the supply efficiency. Establish a quadratic regression model for the efficiency of seed supply and determine the optimal parameter combination: the seed supply belt speed of 0.097 m/s, first conveyor belt speed of 1.639 m/s, and the number of sugarcane seeds is 14. Using the number of sugarcane seeds as the input quantity for the controller, the real-time data is fed back by the TOF sensor. The controller automatically adjusts the seed-cutting efficiency to maintain the continuity and stability of the seed supply process of the seed supply device. The test results show that after applying this system, the seed supply efficiency reached 1.77 setts/s, which was 6% higher than that of the fixed-parameter system. This research can provide technical support for the stable seed supply of integrated equipment for sugarcane seed production.

Li, Shangping, Xu, Hechang, Ouyang, Runhong, Li, Kaihua

An Automatic Assembly System for Digital Direct-Writing Light Source Lens Units

2026-99-0849

7/30/2026

Addressing the challenge of high-precision control requirements for assembly force and displacement during the automatic assembly of digital direct-writing light source lens units, this paper proposes an automatic assembly system design based on impedance control. The system employs torque motors as actuators and achieves dynamic, precise regulation of assembly force and displacement through impedance control with force-displacement coupling. The simulation process consists of three parts: finite element simulation of the assembly system structure, finite element simulation of the assembly process, and MATLAB simulation of impedance control. The finite element simulation of the assembly system structure verifies structural strength and determines deformation values for assembly displacement compensation. A finite element simulation of the assembly process is utilized to investigate the coupling relationship between assembly force and displacement, yielding the coupled force-displacement curves during assembly and determining the theoretical maximum assembly force. The MATLAB simulation of impedance control analyzes parameter settings, including three parameters: theoretical mass, theoretical damping, and theoretical stiffness, in order to ensure the controlled output converges to theoretical values. The main innovation lies in incorporating theoretical maximum assembly force and displacement as impedance control inputs, enabling the force-displacement curve to converge to the theoretical curve, thereby improving assembly quality and precision. The experimental results demonstrate significant improvements in system stability, response speed, and assembly force control precision, effectively enhancing the assembly accuracy and overall efficiency of automated light source production lines. This research provides a viable solution for high-precision assembly of digital direct-writing light source lens units in intelligent manufacturing environments.

Li, Fuduan, Wang, Hua, Wang, Rixin, Zhang, Xianmin

Selected Papers from the 2025 6th International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology

2026-99-0800

7/30/2026

TOC

Tobolski, Sue

Simulation and Experimental Evaluation of a Vehicle–Road Cooperative Positioning Method in Global Navigation Satellite Systems (GNSS)-Denied Environments

12-09-04-0029

7/29/2026

In complex urban environments, vehicle positioning based on Global Navigation Satellite Systems (GNSS) is prone to failure or accuracy degradation due to signal blockage and multipath effects. To address this issue, this article proposes a vehicle–road cooperative positioning method based on factor graph optimization for GNSS-denied environments and evaluates its performance through both simulation and real-vehicle experiments. In the proposed approach, road codes deployed on the road surface serve as absolute position references on the road surface, and high-precision vehicle position estimates are obtained in real time by fusing roadside positioning information with onboard sensor measurements using factor graph optimization. Furthermore, to reduce the experimental cost and development cycle of the vehicle–road cooperative positioning method, a performance simulation platform is developed based on the CARLA simulator, RoadRunner, and the CARLA-ROS (Robot Operating System) bridge for real-time communication between simulation and positioning modules. The platform supports road code generation and deployment, customized scenario construction, and positioning performance simulation, and a multi-objective optimization approach is employed to obtain an optimal deployment scheme for road code spacing. Finally, the effectiveness of the proposed vehicle–road cooperative positioning method is validated through both simulation and real-vehicle experiments. Real-vehicle experiments show that the proposed method reduces the average RMSE (Root Mean Square Error) by 26.6% compared with the ESKF (Error State Kalman Filter) baseline, achieving an RMSE of 0.25 m and a maximum error of 0.95 m at a vehicle speed of 60 km/h and a 10 m code spacing, thereby confirming decimeter-level continuous accuracy in GNSS-denied environments.

Shen, Chuanfu, Zhao, Zhiguo, Yan, Danshu, Ling, Yubin

SAE TOMORROW TODAY - SDVs, AI, and the Next Era of Automotive Innovation

135787/28/2026

What does it really mean to build a software-defined vehicle? As AI reshapes the automotive industry, SDVs may become the foundation for the future rather than the destination. Listen in as we sit down with Jeffrey Chou, Founder and CEO of Sonatus, a leading provider of intelligence-driven SDV solutions, to explore why SDVs are best understood as a platform for innovation -- one that is scalable, upgradable, and proven at scale. This conversation dives into the evolution of SDVs, from over-the-air updates and AI-powered diagnostics to intelligent infrastructure services that could one day allow vehicles to share computing power, storage, and data with the world around them. You'll also get insight on how Sonatus scaled its software, the cultural shift required to bring Silicon Valley and automotive engineering together, and why collaboration -- not competition -- will define the future of mobility. If you're interested in automotive OS, AI, SDVs, or the future of vehicle architecture, this episode offers an insider's perspective on where the industry is headed next. We'd love to hear from you! Share your comments, questions and ideas for future topics and guests podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today-a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.

Patterson, Lori

Performance Analysis and Optimization of a Variable Space Parallel Mechanism

2026-99-1638

7/24/2026

To obtain additional space for industrial sorting and assembly line labeling operations, this study conducts an analysis of the four-bar mechanism. Based on this analysis and combination, the redundant parallel mechanism is introduced. That is, on the basis of the traditional parallel mechanism with central rotation, the objective of expanding the working space is achieved. The degree of freedom of the screw theory and the disparities between the working space of this mechanism and that of the traditional mechanism are analyzed. Finally, through application analysis, it is demonstrated that the working space of this mechanism is variable and that the mechanism can adapt to diverse workplaces.

Li, Wenqian, Zhang, Xiaojie

A Review of Physical and Digital Infrastructure Standards and Guidelines to Support Deployment of Automated Vehicles in Rural Environments

12-09-04-0030

7/23/2026

Connected and Automated Vehicles (CAVs) represent a transformative innovation poised to revolutionize roadway transportation by leveraging automated driving systems equipped with advanced sensors, high-performance computing, and communication technologies. While urban areas are the primary focus of current CAV developments, rural transportation systems risk being left behind despite the significant benefits that CAVs can bring to these regions. This article, therefore, explores the physical and digital infrastructure requirements for the safe deployment of CAVs in rural areas, drawing insights from standards, recommendations, and guidelines developed by leading standard organizations. The study highlights the specific design of physical infrastructure, including traffic signs, traffic signals, and pavement markings, and digital infrastructure, including communication, sensing, and mapping, to ensure rural communities are effectively prepared to benefit from the potential of CAVs. As its primary contribution, this article provides a comprehensive review of existing standards and guidelines relevant to rural CAV deployment. By synthesizing guidance across multiple standard-setting organizations, this review delivers a structured analytical assessment of existing standards, revealing their limitations and misalignment with rural transportation contexts while highlighting emerging good practices. The article clarifies the applicability of current guidance to rural infrastructure, identifies systemic infrastructure-related failure modes, and informs context-aware planning considerations for efficient and scalable CAV deployment in rural areas.

Zakaria, Mohammed, Getahun, Tesfamichael, Tavasoli, Mahsa, Pandey, Venktesh, Sarrafzadeh, Abdolhossein, Karimoddini, Ali

North American CAV Performance Data Standard

WP-00157/22/2026

As the deployment of connected and automated vehicles (CAVs) expands, the need for a consistent, cross-industry approach to performance relevant CAV data exchange is becoming more pressing. Vehicle developers, infrastructure owners and operators (IOOs), and technology providers generate and consume data that support safety, mobility, and operational efficiency, yet much of the data remains fragmented, inconsistently formatted, and difficult to reuse across systems. To address these gaps, the Society of Automotive Engineers (SAE) and the Canadian Standards Association (CSA) convened a multi-stakeholder workshop on November 3, 2025, with participants representing original equipment manufacturers (OEMs), automated driving system (ADS) developers, state and local agencies, standards bodies, and technology partners. The workshop focused on identifying challenges, clarifying needs, and outlining a path toward a North American CAV Performance Data Standard. Key themes from the workshop included: -The need for a shared data language to support safe and interoperable CAV operations. -The lack of consistent formatting, labeling and visibility regarding who produces and consumes data. -A “start small, iterate and scale” approach beginning with well-defined use cases. -The need for technical harmonization and governance structures that build trust and support sustained coordination. This white paper summarizes the key findings and outlines a practical approach to developing a Version 0.1 base-layer data standard that can support measurable progress in 2026 and beyond.

Nesheli, Mahmood

Automated Driving Fallback Test Driver Skill Certification

J3300/3_202607 (Current)

7/20/2026

This document is intended to establish a procedure to certify AD fallback test driver skill levels as an endorsement to SAE J3300 foundational level certification. The SAE J3300/3 endorsement can be used by the individual driver to qualify their skills as a test driver of vehicles with automated driving features. The SAE J3300/3 endorsement levels may also be used by test facilities or other organizations when seeking test or professional drivers with these skills. This document provides directions for obtaining the endorsement, including associated AD fallback test driving skill examination requirements, through SAE J3300-certified Examiners (refer to SAE J3300 for definition). Endorsement registration and associated records are administered through Probitas Authentication®. Probitas Authentication® is the current Independent Program Administrator for the SAE J3300 series. This document is a supplement to SAE J3300, providing information specific to the AD fallback test driver skill endorsement and clarifying the application of the rules set forth in SAE J3300 to the AD fallback test driver endorsement. While the references, definitions, rules, and guidelines presented in SAE J3300 Sections 1 through 5 apply to the AD fallback test driver endorsement, they are not repeated in this document.

Driving Skills Standards Committee

Research on Clustering Data-Driven Intelligent Perception Algorithm for Micro Mobile Robots

2026-99-1843

7/17/2026

To address the challenges faced by micro flapping-wing flying robots in visual navigation—specifically, the large volume of visual information and the difficulty in transforming it into usable intelligent visual data—this paper proposes a clustering-based data-driven approach for directional and image perception. The aim is to enable intelligent visual navigation for flapping-wing robots. The proposed method performs clustering analysis on gyroscope data from the flapping-wing robot to extract directional features. Simultaneously, it applies clustering techniques to visual images captured by the robot to identify intelligent features such as edges. This approach enables the robot to acquire multiple optimized perceptual data types, thereby enhancing the behavior control system. Through the use of clustering analysis, the method not only improves the effectiveness of visual navigation but also extracts features related to visual targets and environmental information, providing technical support for visual target tracking. The experimental platform consists of a flapping-wing robot equipped with an onboard camera, and the proposed clustering-driven visual image perception approach has been experimentally validated. Experimental results demonstrate the high feasibility and effectiveness of the method in practical applications. The main contributions of this study lie in two aspects: (1) a clustering-driven visual image perception method for flapping-wing robots, and (2) a clustering-based approach for identifying posture and behavioral patterns of flapping-wing flying robots.

Li, Zixuan, Ding, Wei, Zhang, Feng, Song, Min, Liu, Zhaoming, Miao, Lei, Liu, Haotian, Bai, Ning, Tian, Shen, Cui, Long, Wang, Hongwei

Automatic Synthetic Road Network Drivability Evaluation

2026-01-5042

7/13/2026

Simulation plays a significant role in the validation and verification of Automated Driving Systems (ADS). In a scenario-based validation strategy, the road and the actions of the traffic participants must be captured in a portable and flexible format for simulation. XML-based parametric models constitute a common combination upon which the static and dynamic aspects of the environment are captured. Although there are plenty of tools for generating these XML files there are few alternatives to verify their content. This paper suggests a method for converting and simplifying a synthetic road network into a graph for which the Chinese Postman Problem is solved. The resulting sequence can be converted back into a route that can be sampled to verify the drivability of the whole network. Once the network is verified, it can be safely used for simulation, increasing the speed at which ADS systems are developed. The graph representation can also be used to provide interactive feedback to LLMs (Large Language Model), which are increasingly used for automatic generation of roads and scenarios.

Vargas Rivero, Jose Roberto, Kern, Andreas, Menken, Stefan, Harth, Michael, Kuipou, Franck Russel

Validation and Exploration of Multimodal Deep-Learning Camera–LiDAR Calibration Models

2026-01-5037

7/13/2026

This paper presents an innovative study in exploring, evaluating, and implementing deep-learning architectures for the calibration of multimodal sensor systems. The aim of this paper is to leverage the use of sensor fusion to achieve dynamic, real-time alignment between 3D LiDAR and 2D camera sensors. Static calibration methods are tedious and time-consuming, which is why we propose utilizing conventional neural networks (CNNs) coupled with geometrically informed learning to solve this issue. We leverage the foundational principles of extrinsic LiDAR–camera calibration tools such as RegNet, CalibNet, and LCCNet by exploring open-source models that are available online and compare our results with their corresponding research papers. Requirements for extracting these visual and measurable outputs involved tweaking source code, fine-tuning, training, validation, and testing of each of these frameworks for equal comparisons. This approach aims to investigate which of these advanced networks produces the most accurate and consistent predictions. Through a series of experiments, we reveal some of their shortcomings and areas for potential improvements. We find that LCCNet yields the best results among all the models that we validated.

Karramreddy, Venkat Sai Raxit, Mitchell, Liam

Optimizing Autonomous Obstacle Avoidance with PON Architecture and SDN-Based Dynamic Scheduling

2026-99-0592

7/10/2026

This study addresses the challenges of communication delays and system stability in autonomous obstacle avoidance (AOA) systems under next-generation vehicular electronic/electrical architectures. A centralized PON-based architecture is proposed, leveraging XGSPON technology to enhance bandwidth capacity and reduce electromagnetic interference, while rigorously analyzing worst-case in-vehicle communication (IVOC) delays. To mitigate latency impacts, a Software-Defined Networking (SDN)-driven dynamic scheduling strategy prioritizes safety-critical data streams (e.g., environmental perception, motion control) through adaptive resource allocation. Further integrated with a robust H-infinity LQR controller, the co-design framework ensures precise trajectory tracking and suppresses steering oscillations under communication uncertainties. Simulation tests validate the framework's efficacy, demonstrating significant reductions in loop delays and improved dynamic stability in complex scenarios. This work bridges communication efficiency and control robustness, offering a scalable solution for advancing safety-critical autonomous driving systems.

Wang, Wenwei, Han, Muchen, Cao, Wanke

A Framework for Precautionary Safety for Automated Driving Systems—Toward Tactical Decisions Fulfilling Quantitative Risk Acceptance Criteria

12-09-04-0028

7/8/2026

Safety of Automated Driving Systems (ADSs) is arguably one of the main remaining barriers before widespread market deployment. While there exists a plethora of methods for planning a trajectory that fulfils certain constraints, what those constraints should look like, to enable effective planning of safe trajectories, is still being discussed. In this article, we generalize the concept of Precautionary Safety (PCS) and present a framework providing constraints on the tactical and operational decisions of the ADS. Such constraints consider the ADS’ capabilities, the external conditions, knowledge of statistically relevant events and behaviors of other traffic actors, as well as the controllability of these events. The proposed framework enables assessment of the statistical fulfilment of quantitative risk acceptance criteria (QRACs), including requirements on accident, injury, and fatality rates. The framework further provides a means to dynamically adapt the constraints used for trajectory planning, i.e., to adapt the driving to the situation at hand. A case study, considering a possible collision scenario with a jaywalking pedestrian and a rear-end collision with a trailing vehicle, is provided to showcase the applicability and usefulness of the presented framework. The simulation-based case study displays the safety benefits from considering QRACs with multiple injury risk levels and further shows how the proposed PCS framework can be applied in practice.

Gyllenhammar, Magnus, de Campos, Gabriel Rodrigues, Sandblom, Fredrik, Törngren, Martin, Fredriksson, Jonas

Cybersecurity Risk Assessment and Experimental Validation of Automotive Ultrasonic Sensors

2026-01-0782

7/1/2026

Ultrasonic sensors are widely deployed in automotive driver assistance systems for near-range environment perception and provide safety-relevant inputs for functions such as parking assistance and automated parking. With increasing vehicle automation, the integrity and availability of ultrasonic sensor data become more critical, as compromised measurements may lead to incorrect vehicle decisions and hazardous behavior. While prior research has extensively studied physical attacks on ultrasonic sensors, a structured cybersecurity risk analysis in accordance with automotive cybersecurity standards, combined with experimental validation, is largely missing. In particular, the communication interface between ultrasonic sensors and control units has received limited attention despite its relevance as a potential attack surface. This paper presents a systematic security analysis of an automotive ultrasonic sensing system based on a demonstrator setup. The work applies a Threat Analysis and Risk Assessment methodology aligned with ISO/SAE 21434 and HEAVENS 2.0 to identify security-relevant assets, threat scenarios, and attack paths. Risk levels are derived by evaluating potential impact and attack feasibility. To validate the risk assessment, a structured test strategy is developed using the ISTQB test process and translated into laboratory experiments. Both digital attacks targeting the sensor communication interface, with DSI3 selected as the representative protocol, and physical manipulations of the sensor environment are examined. Experimental results show that selected communication-level attacks can be realized with moderate effort and can cause controlled falsification or loss of measurement data. Physical environmental manipulations significantly degrade signal quality but do not fully suppress object detection in the evaluated configuration. The findings largely confirm the initial risk assessment while enabling refinement of attack feasibility parameters. The results provide a validated linkage between automotive cyber-security risk assessment methods and practical testing of ultrasonic sensing systems and underline the importance of jointly addressing communication interfaces and physical effects in future security concept development.

Gahm, Sebastian, Haller, Jonathan, Kriesten, Reiner

Stakeholder-Oriented Explainability Requirements for Advanced Driver Assistance Systems and Automated Driving Systems: A Structured Analysis

2026-01-0788

7/1/2026

The development and validation of advanced driver-assistance systems (ADAS) and automated driving systems (ADS) are shifting from traditional linear V-model processes toward more iterative engineering cycles. Despite faster iteration, these safety-critical systems remain subject to stringent regulations. Standards and guidance, including UNECE UN Regulation No. 157 and ISO/TS 5083, emphasize traceability, transparency, and explainability throughout development and validation. Nevertheless, as ADAS/ADS are developed and validated in faster, more iterative release cycles, additional stakeholders become involved and new explainability requirements emerge. These requirements vary between stakeholders and across development, validation, and post-market deployment phases, yet they are not systematically captured in the current state of research and practice. Therefore, to ensure that explainability supports rapid iteration, it is essential to identify relevant stakeholders and specify their explainability needs. Standards such as IEEE Standard 7001-2021 provide a broad foundation for transparency in autonomous systems. However, their generic nature does not address the domain-specific complexities of ADAS/ADS. Furthermore, a conceptual gap remains between general transparency principles and explainability requirements in automotive development and validation. Building on IEEE Standard 7001-2021, this paper first offers a stakeholder taxonomy in the context of ADAS/ADS, then proposes a stakeholder-oriented analysis of explainability requirements within an automated driving use case and contexts. This analysis specifically focuses on the motivations for requiring explainability and the necessary explanation modalities. Finally, the paper discusses the limitations of the analysis and outlines directions for future research. The results of the paper provide a structured guideline for stakeholder-oriented explainability requirements in ADAS/ADS.

Liu, Xuanheng, Bairy, Akhila, Paudel, Bijay, Adolph, Laurenz, Heck, Melanie, Hettich, Lennard, Nägele, Ann-Therese, Rudolf, Korbinian, Bause, Katharina, Düser, Tobias, Schwammberger, Maike

Context-Dependent Assessment of Driving Dynamics and User Perception in Automated Driving

2026-01-0757

7/1/2026

As automation advances and occupants transition from active drivers to passive passengers, understanding how automated driving behavior is evaluated becomes increasingly important. While longitudinal and lateral vehicle dynamics are known to influence perceived comfort and safety, it remains unclear to what extent motion–perception relationships remain stable across urban traffic contexts. This study compares two real-world investigations of automated driving: a left-turn maneuver at a signalized intersection on a test track and a roundabout maneuver with a shuttle in public traffic. Both datasets include high-resolution vehicle dynamics and structured subjective ratings. A consistent objectification approach was applied to examine the transferability of motion–perception relationships across contexts. However, differences in vehicle platform, automation level, trajectory characteristics, and study design limit direct comparability and require cautious interpretation. Despite partially overlapping ranges in selected peak-based dynamic parameters, such as longitudinal acceleration, subjective comfort and safety ratings were consistently higher in the roundabout scenario. Furthermore, strong associations were observed between motion parameters and subjective evaluations in the intersection context (adj. R2 up to 0.891), whereas objective parameters showed only limited explanatory power in the roundabout scenario (adj. R2 ≤ 0.06). The results indicate that motion–perception relationships derived within a specific context may not be directly transferable across different traffic scenarios. The findings highlight limitations of globally derived motion-based evaluation models and underline the importance of validating objectification approaches across diverse operational environments.

Panzer, Anna, Strenge, Emma, Iatropoulos, Jannes, Henze, Roman

Route-Based Sensor-Aware Speed Planning and Support for Safety Validation for Level-3 Automated Driving

2026-01-0772

7/1/2026

Level-3 and higher automated driving systems require longitudinal speed strategies that remain consistent with both physical stopping feasibility and realistic sensing constraints. This paper presents a route-based, sensor-aware speed planning method that supports safety validation and explicitly couples longitudinal driving strategy with sensor field-of-view coverage. Based on a concrete route extracted from digital maps and enriched with fleet data, point-wise maximum speeds are computed considering road curvature, speed limits, and comfort constraints. From the resulting drivable speed profile, physically consistent stopping paths and their endpoints are calculated for each route position, accounting for friction limits, scenario-dependent deceleration capabilities, and system delays between perception and braking. The set of stopping paths is aggregated into a region of interest (ROI) representing the spatial area that must be reliably perceived to guarantee safe stopping. This ROI is overlaid with the geometric fields of view of camera, radar, and lidar sensors, enabling the definition of a compact and interpretable key performance indicator (KPI) based on the number of sensor modalities covering critical regions. Rather than evaluating a specific sensor configuration, the proposed KPI establishes a geometric interface between braking-based perception requirements and multi-modal sensing coverage. The approach reveals the structural sensitivity of perception demands to route geometry and braking assumptions and provides a systematic basis for perception-aware speed release decisions. The method is applicable to highways, interchanges, and other route types, and contributes a modular geometric framework for sensor-aware safety analysis in Level-3 and higher automated driving systems.

Kohler, Paul Leonhard, Resch, Michael

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