To address the issues of large storage requirements in maps and the dependence of localization accuracy on initial pose estimation, this paper proposes a novel relocalization method named LLS-SMGSC, which is based on simplified maps integrated with Global Search capabilities. Firstly, we partition the map-based on grid size to reduce memory usage. Next, we voxelize the point cloud and map and extract surfel. Then, a coarse-to-fine hierarchical alignment module between the initial frame and maps to estimate the initial global pose. Finally, unmanned platform pose is estimated by the Normal Distribution Transform (ndt) algorithm. Experiments demonstrate that LLS-SMGSC achieves the highest localization accuracy in both unstructured and structured environments while maintaining computational efficiency.

Quan, Zhiheng

Research and Implementation of a Neural Radiance Fields-Based 3D Reconstruction Method for Autonomous Driving Scenes

2025-01-7310

12/31/2025

This paper addresses the scarcity of training and testing data in autonomous driving scenarios. We propose a 3D reconstruction framework for autonomous driving scenes based on Neural Radiance Fields (NeRF). Compared to traditional multi-view geometry methods, NeRF offers superior scene representation and novel view synthesis capabilities but suffers from low training efficiency and limited generalization. To overcome these limitations, we integrate existing NeRF optimization techniques and introduce a scene-specific data reuse strategy tailored for autonomous driving, enabling continuous 3D reconstruction directly from 2D images without requiring elaborate calibration. This approach significantly improves reconstruction efficiency, achieving reliable reconstruction and real-time visualization in complex traffic environments. Furthermore, we develop an interactive scene editing plugin in Unreal Engine 5, supporting the addition, removal, and adjustment of static objects. This extension

Pan, Deng, Zou, Jie, Chen, Yuhan, Meng, Zhangjie, Li, Jie, Li, Guofa

STO-VINS: A Robust Monocular Visual-Inertial SLAM Based on a Fusion Feature Extraction Algorithm Combining Shi-Tomasi and ORB

2025-01-7306

12/31/2025

The VINS-Mono algorithm, which is based on a visual-inertial SLAM framework, faces challenges in extracting feature points in regions with weak or repetitive textures and struggles to achieve accurate localization under unstable lighting conditions. This paper proposes STO-VINS, a robust monocular visual-inertial SLAM algorithm that introduces several key innovations in feature extraction. Key innovations of STO-VINS include: (1) an adaptive multi-scale image preprocessing pipeline that combines image scaling, CLAHE enhancement, and Gaussian filtering, reducing computational complexity by 64% while maintaining feature quality; (2) bidirectional Lucas-Kanade optical flow consistency verification with geometric constraint validation, which significantly reduces false tracking rates by 30-40%; (3) a grid-based multi-feature fusion detection strategy combining Shi-Tomasi corner detection and ORB feature extraction, ensuring uniform spatial distribution of features and feature diversity; (4

Li, Jing, Wu, Jing, Liu, Bo, Gong, Zeyuan, Zhang, Guofang

MAF-NET: A Multi-Scale Feature Fusion Network for Low-Light Driving Image Enhancement

2025-01-7304

12/31/2025

In low-light driving scenarios, in-vehicle camera images encounter technical challenges, including severe brightness degradation and short exposure times. Conventional driving image enhancement algorithms are susceptible to issues such as the loss of image features and significant color distortion. The proposed solution to this problem is a multi-scale attention fusion network (MAF-NET) for the enhancement of images captured during low-light driving conditions. The network’s structural design is uncomplicated. The model incorporates a meticulously designed multi-scale attention fusion module (MAFB), along with all essential components for network connectivity. The MAF is predicated on a heavy parameter residual feature block design and incorporates a multi-scale channel attention mechanism to capture richer global/local features. A substantial body of experimental evidence has demonstrated that, in comparison with prevailing algorithms, MAF-NET exhibits superior performance in low

Pan, Deng, Chen, Yuhan, Shi, Yicui, Li, Jie, Li, Guofa

Detection of Dangerous Driving Postures Based on Depth Images Using an Anchor Regression Method

2025-01-7343

12/31/2025

Perceiving the movement characteristics of specific body parts of a driver is crucial for determining their activity. Moreover, the driver’s body posture significantly impacts personnel safety during collision. This study investigates the creation of a dataset using Kinect depth camera for acquiring, organizing, annotating with skeleton tracking assistance, and optimizing interpolation. The pose recognition methods enhanced through an anchor regression mechanism, leading to the refinement of a lightweight anchor regression network capable of end-to-end learning ability from depth images. The improved backbone neck head structure offers advantages of reduced model parameters and enhanced accuracy. This engineering optimization makes it better suited for practical applications within vehicles with limited computational resources limitations and high real-time demands.

Xu, Hailan, Li, Wuhuan, Lu, Jun, Wang, Xin, He, Wenhao, Chen, Zhenming, Liu, Yunjie

GP-LGFusion: Deep Fusion of Infrared-Visible Driving Images Based on Gradient Preservation and Local Guidance

2025-01-7305

12/31/2025

Infrared and visible driving image fusion represents a pivotal technology in multi-source perception for automated driving. The objective of this technology is to generate fused images that exhibit significant targets and comprehensive road information in complex traffic scenes. However, the existing image fusion algorithms demonstrate inconsistent capacity to complement information in diverse environments. Additionally, there are limitations in their ability to extract features, such as the detailed texture of traffic targets under complex lighting conditions, including low-light scenes and multi-exposure scenes. To overcome these limitations, we propose a novel gradient-preserving and locally guided fusion method (GP-LGFusion). Our primary contribution is a Multi-scale Gradient Residual Block (MGRRB), an encoder module specifically designed to capture and retain both strong and weak texture features across different scales, a capability lacking in conventional approaches. Second, we

Meng, Zhangjie, Shi, Yicui, Chen, Yuhan, Zhou, Xiaoji, Li, Jie, Li, Guofa

Long-Term Temporal Hierarchical Fusion Bird’s-Eye View Perception Method Based on Multiple Position Encodings

2025-01-7307

12/31/2025

With the rapid development of autonomous driving technology, environmental perception, as its core module, has attracted much attention. Among them, the pure visual bird's-eye-view (BEV) 3D detection scheme has become a research hotspot due to its high spatial resolution and excellent semantic recognition ability in specific scenarios. Existing methods mainly utilize the Transformer encoder structure to perform position encoding in the BEV domain to achieve 3D perspective transformation, but they often fail to fully exploit the potential value of multi-perspective image information. To address this challenge, this paper proposes an improved Transformer-based visual BEV vehicle perception method that enhances perception performance by deeply fusing BEV domain and image domain information: an innovative multi-perspective position encoding mechanism is designed, which decouples camera parameters to more efficiently learn the mapping from images to 3D space; at the same time, a cyclic

Chen, Pengyu, Wei, Xiaoxu, Chen, Zhenwei

Impact of Tire-Ground Contact Width on Pavement Roughness Evaluation

2025-99-0256

12/23/2025

The International Roughness Index (IRI) is a key indicator for evaluating the performance of road surfaces. However, traditional measurement methods only focus on the evaluation data of a single longitudinal section and do not consider the lateral difference between the actual contact area between the tire and the road surface, which may lead to inaccurate evaluation results. In recent years, with the advancement of 3D laser scanning and digital photogrammetry technology, full-section data acquisition has brought new possibilities for roughness evaluation. However, how to find a balance between data fineness and computing efficiency has become a core problem that needs to be solved. Based on the principle of interaction between vehicles and road surfaces, this paper proposes to include only the pavement height data within the tire width range into IRI analysis, and establishes an evaluation framework based on standard tire-ground contact width. This method not only retains the key

An, Huazhen, Wang, Rui, Han, Xiaokun, Luo, Yingchao

Trajectory Reconstruction at Signalized Intersections in a Vehicle-to-Infrastructure Environment

2025-99-0217

12/23/2025

Vehicle trajectories encapsulate critical spatial-temporal information essential for traffic state estimation, congestion analysis, and operational parameter optimization. In a Vehicle-to-Infrastructure (V2I) environment, connected automated vehicles (CAVs) not only continuously transmit their own real-time trajectory data but also utilize onboard sensors to perceive and estimate the motion states of surrounding regular vehicles (RVs) within a defined communication range. These multi-source data streams, when integrated with fixed infrastructure-based detectors such as speed cameras at intersections, create a robust foundation for reconstructing full-sample vehicle trajectories, thereby addressing data sparsity issues caused by incomplete CAV penetration. Building upon classical car-following (CF) theory, this study introduces a novel trajectory reconstruction framework that fuses CAV-generated trajectories and infrastructure-based speed detection data. The proposed method specifically

Bai, Wei, Fu, Chengxin, Yao, Zhihong

Analysis of Light Duty Vehicle Particulate Matter Emissions Using Scanning Electron Microscopy

2025-36-0074

12/18/2025

Particulate matter (PM), mainly its finer fraction, is among the main atmospheric pollutants present in an urban environment. The relationship between the increase in the concentration of this pollutant and the harm to human health is well established. The main sources of particulate matter in urban areas are mobile sources, which include the exhaust emission from light duty vehicles. This work measured the emission of PM in three light duty passenger vehicles, characterizing it in terms of emitted mass in one “flex” vehicle with port fuel (indirect) injection (PFI), using ethanol and gasohol (mixture of 22% anhydrous ethanol and 78% gasoline, by volume), in another “flex” vehicle with direct fuel injection (GDI), and in a diesel vehicle. In addition to mass measurement, images of the filters used in PM sampling were produced using scanning electron microscopy. The processing of these images made it possible to determine the average PM size, as well as establish a particle size

Borsari, Vanderlei, Neto, Edson Elpídio, de Abrantes, Rui

Development of Embedded Electronics with Artificial Intelligence in an Implement for Forklifts

2025-36-0012

12/18/2025

In this article we will discuss the development and implementation of a computer vision system to be used in decision-making and control of an electro-hydraulic mechanism in order to guarantee correct functioning and efficiency during the logistics project. To achieve this, we have brought together a team of engineering students with knowledge in the area of Artificial Intelligence, Front End and mechanical, electrical and hydraulic devices. The project consists of installing a system on a forklift that moves packaged household appliances that can identify and differentiate the different types of products moved in factories and distribution centers. Therefore, the objective will be to process this identification and control an electro-hydraulic pressure control valve (normally controlled in PWM) so that it releases only the hydraulic pressure configured for each type of packaging/product, and thus correctly squeezing (compressing) the specific volume, without damaging it due to

Furquim, Bruno Bueno, Pivetta, Italo Meneguello, Ibusuki, Ugo

Nanosilica-Based Treatments for Fabrics: Aspects of Wettability and Selective Oil/Water Separation

2025-36-0213

12/18/2025

Nanosilica-treated fabrics have a variety of properties, such as durability, water resistance, and specific surface characteristics. Due to that, many applications of those components are highlighted in literature. Some examples include waterproofing and water repellency, stain resistance, flame retardancy, improved durability, UV protection, improved comfort, antimicrobial properties, and textile coatings for electronics. These applications demonstrate how nanosilica-based treatments can enhance the performance of fabrics, making them more suitable for various specialized uses. In this work, a technical fabric with a mesh opening of 45 μm and an open area of 29.6% was surface treated. The treatments were performed by the dip-coating method using poly(dimethylsiloxane) (PDMS) and nanosilica at different concentrations. Optical microscopy (OM) images of the fabrics’ surface and water contact angle (WCA) measurements were carried out before and after the fabrics’ treatments. The results

Kerche, Eduardo Fischer, Leal, Débora, Romano, Paulo, Oliveira, Vinícius, Polkowski, Rodrigo

Evaluation of Surface Integrity Aspects Induced by Different Gear Manufacturing Paths for Electric Vehicle Transmission Systems

2025-36-0062

12/18/2025

The mobility electrification process is currently of great interest due to its environmental appeal, but it is accompanied by new technical requirements for vehicle systems, the powertrain being one of those with the most significant trade-offs to be solved. Higher power densities, higher torque efficiency and lower noise and vibration generation are simultaneously required. The literature shows that the manufacturing chain can influence the final state of surface integrity of a part, which affects the operational behavior and service life of a component. Therefore, a customized transmission system design for electric propulsion requires several analyses, from the raw material to the gear manufacturing processes, so that surface integrity plays a significative role in the required performance. From the perspective of their capability to meet the e-mobility requirements in terms of surface integrity is essential to conduct a comparative analysis of gear manufacturing processes. So, the

Gomes, Caio F. S., Gomes, Gilberto M. O., Colombo, Tiago C. A., Rego, Ronnie R., Michelotti, Alvaro C., Berto, Lucas F.

Fractographic Analysis after Creep Testing of Ti-6Al-4V with Yttria and Niobia Co-Doped Zirconia TBC

2025-36-0053

12/18/2025

The application of Thermal Barrier Coatings (TBC) has been widely utilized in aerospace turbines to enhance the operational temperature and thermal efficiency of titanium alloys, while preserving their properties such as low density, creep resistance, and corrosion resistance. TBC systems typically consist of a metallic substrate, a metallic coating (Bond Coat), a thermally grown oxide (TGO), and a ceramic topcoat (TC). This study investigated the fracture surface characteristics of Ti-6Al-4V with TBC after a creep test at a constant temperature of 600 °C, under stress levels of 125, 222, and 319 MPa, in order to understand the mechanisms involved. The TBC was composed of a NiCrAlY (BC) and a zirconia co-doped with yttria and nióbia (TC). The fracture characterization of the alloy after the creep test was conducted through stereoscopy and scanning electron microscopy. The fracture mechanism at 600 °C and 222 MPa was predominantly ductile, as evidenced by the presence of dimples and

Takahashi, Renata Jesuina, de Assis, João Marcos Kruszynski, Rodrigues, Bianca Costa, de Andrade Acevedo Jimenez, Laila Ribeiro, Reis, Danieli Aparecida Pereira

Optimization Method for the Layout of Sponge-Like Drainage Ditches in Large Airports Based on BIM-3DGIS Coupling

2025-99-0356

12/17/2025

The control of rainfall runoff drainage in large airports presents significant challenges, particularly in terms of real-time coupling with meteorological warnings. This paper proposes an optimization method for the layout of sponge-like drainage ditches in large airports under BIM-3DGIS coupling. A BIM water supply and drainage model is constructed, with detailed inspections conducted on the functions and connections of the pipeline system in Revit software. The flow velocity and equivalent water supply pressure within the pipelines are analyzed, and collision detection is performed on the components. Based on 3DGIS technology, an optimization model for the layout of sponge-like drainage ditches is established, taking into comprehensive consideration various factors such as airport topography, rainfall characteristics, and surrounding environment. By calculating the water level changes within the infiltration and drainage ditches under different design rainfall scenarios, the storage

Geng, Liangsui, Zhao, Zhenyu, Hu, Jing

Dynamic Graph Convolutional Recurrent Networks Based on Progressive Learning

2025-99-0441

12/10/2025

Traffic flow prediction is the core challenge of transportation, and its key lies in effectively capturing the spatio-temporal dynamic dependencies. Aiming at the deficiencies of existing methods in modeling global temporal relations and dynamic spatial heterogeneity, this paper proposes a dynamic graph convolutional recurrent network (DGCRN) based on interactive progressive learning. First, the interactive progressive learning module (IPL) is designed to segment the input sequences through a tree structure, synchronize the extraction of spatiotemporal features using the interactive learning of parity subsequences, and adaptively capture the dynamic associations among nodes by combining with the dynamic graph convolutional recursive module (DGCRM). Secondly, a spatio-temporal embedding generator (STEG) is constructed to fuse temporal and spatial embedding to generate dynamic graph structures. Experiments validate the effectiveness of DGCRN on the PEMS04 and PEMS08 datasets with MAE

Su, Jiangfeng, Xie, Zilong, Liu, Chunya, He, Lan, Kou, Yujiao, Xue, Xue

EDITORIAL: Off-highway innovators help kick off 2026

25TOFHP12_04

12/01/2025

As I'm wont to do come December, with work well underway on the first issue of the new year, I like to take stock of upcoming venues for innovative product reveals and thought-provoking presentations on emerging trends and technologies. Come the first week of January, that means CES in Las Vegas. Traditional equipment manufacturers have increasingly used the event to demonstrate to the broader public that they not only deal in metal but also the digital realm. For example, earlier this year at CES, John Deere revealed its second-generation tech stack featuring camera pods, Nvidia Orin purpose-built processors and Deere's VPUs (vision processing units), along with four new autonomous machines including the 9RX 640 tractor for open-field ag operations. The company is exhibiting again this coming year.

Gehm, Ryan

How Metasurfaces Can Act as Quantum Upgrades

TBMG-54292

12/01/2025

In the race toward practical quantum computers and networks, photons — fundamental particles of light — hold intriguing possibilities as fast carriers of information at room temperature. Photons are typically controlled and coaxed into quantum states via waveguides on extended microchips, or through bulky devices built from lenses, mirrors, and beam splitters. The photons become entangled — enabling them to encode and process quantum information in parallel — through complex networks of these optical components. But such systems are notoriously difficult to scale up due to the large numbers and imperfections of parts required to do any meaningful computation or networking.

Training Uncrewed Underwater Vehicles for Visualization of Subsurface Structures

TBMG-54290

12/01/2025

Stoneridge Innovation Truck envisions a digital-vision future

25TOFHP12_05

12/01/2025

Stoneridge displayed its vision for the future of commercial vehicle technology on the SAE COMVEC 2025 exhibit floor. The Innovation Truck showcases the Tier 1 supplier's next-generation vision and driver-assistance technologies designed to enhance driver safety and fleet optimization. Mario Gafencu, product design and evaluation specialist at Stoneridge, gave Truck & Off-Highway Engineering a tech truck walkaround at the event. The first technology Gafencu detailed was the second-generation MirrorEye camera monitor system that's designed to replace the glass mirrors on the sides of a truck.

Gehm, Ryan

Entangled-Photon Pairs Secure Optical Communications

TBMG-54294

12/01/2025

NASA’s Glenn Research Center has developed a method of using entangled-photon pairs to produce highly secure mobile communications that require mere milliwatts of power. Conventional gas Argon-ion laser sources are too large, expensive, and power-intensive to use in portable applications. By contrast, Glenn’s patented optical quantum communication method produces entangled-photon pairs approximately a million times more efficiently than conventional sources, in a system that is small and light enough to be portable.

Color Filtering Software Enhances Material Strain Analysis

TBMG-54293

12/01/2025

Innovators at NASA Johnson Space Center have developed a technology that can isolate a single direction of tensile strain in biaxially woven material. This is accomplished using traditional digital image correlation (DIC) techniques in combination with custom red-green-blue (RGB) color filtering software. DIC is a software-based method used to measure and characterize surface deformation and strain of an object. This technology was originally developed to enable the extraction of circumferential and longitudinal webbing strain information from material comprising the primary restraint layer that encompasses inflatable space structures.

3D LiDAR for Improved Rover Traversal and Imagery

TBMG-54295

12/01/2025

Planetary and lunar rover exploration missions can encounter environments that do not allow for navigation by typical, stereo camera-based systems. Stereo cameras meet difficulties in areas with low ambient light (even when lit by floodlights), direct sunlight, or washed-out environments. Improved sensors are required for safe and successful rover mobility in harsh conditions. NASA Goddard Space Flight Center has developed a Space Qualified Rover LiDAR (SQRLi) system that will improve rover sensing capabilities in a small, lightweight package. The new SQRLi package is developed to survive the hazardous space environment and provide valuable image data during planetary and lunar rover exploration.

Visualization of Ammonia Engine by Pre-Chamber Igniter

2025-01-0530

11/25/2025

Ammonia is considered more and more as a promising carbon-free fuel for internal combustion engines to contribute to the decarbonization of several sectors where replacing conventional engines with batteries or fuel cells remains unsuitable. However, ammonia properties can induce some challenges for efficient and stable combustion. This study investigates the use of an active pre-chamber ignition system fueled with hydrogen and compares it to conventional spark ignition, with a focus on lean limit operation and early flame development. Experiments were conducted on a single cylinder optical engine with a compression ratio of 9.5, equipped with a quartz window in the piston for natural flame luminosity imaging using a high-speed camera. The engine was fueled with a mixture of 95% ammonia and 5% hydrogen by volume. Ammonia was injected and mixed with air in the intake port while hydrogen was directly injected into the prechamber. As a function of the intake pressure (1.0, 0.9, 0.8, and

Rousselle, Christine Mounaim, Brequigny, Pierre, Gelé, Raphaël, Moreau, Bruno

Ultra-Lightweight, Multispectral, High-Resolution Imaging for Orbital Intelligence and Civilian Missions

TBMG-54192

11/18/2025

Elbit Systems Haifa, Isreal

An AI-Powered Wearable Device to Expedite Wound Healing

TBMG-54140

11/12/2025

Waiting for a wound to heal is incredibly frustrating. First, it must clot; then an immune system response is needed; followed by scabbing and scarring — and that’s not even getting into the pain part.

Research on Overspeed Vehicle Detection Based on Fusion of Millimeter-Wave Radar and Visual Images

2025-99-0129

11/11/2025

To address the limitations of conventional overspeed detection methods, this study proposes a vehicle overspeed detection approach based on the fusion of millimeter-wave radar (MWR) and vision sensors. The MWR captures target position and velocity data, while the vision sensor acquires vehicle image information. Radar-detected points are mapped onto visual images through coordinate transformation, and the Intersection over Union (IoU) method is employed to associate radar points with vision-detected vehicle bounding boxes. Subsequently, for radar-detected points exceeding the speed threshold, the corresponding vehicle images are identified, enabling real-time overspeed detection and data acquisition. This method not only facilitates prompt identification of speeding behavior but also extracts the associated vehicle images, ensuring both accuracy and informational integrity in overspeed monitoring. Experimental results demonstrate that the proposed method achieves high speed measurement

Li, Yuanchen, Wu, Zhichao, Xu, Haibo, Song, Liangliang, Huang, Hao

Virtual Reality Application in CFD Data Analysis for after Treatment Systems

2025-28-0329

11/06/2025

Virtual reality (VR), Augmented Reality (AR) and Mixed reality (MR) are advanced engineering techniques that coalesces physical and digital world to showcase better perceiving. There are various complex physics which may not be feasible to visualize using conventional post processing methods. Various industrial experts are already exploring implementation of VR for product development. Traditional computational power is improving day-by-day with new additional features to reduce the discrepancy between test and CFD. There has been an increase in demand to replace actual tests with accurate simulation approaches. Post processing and data analysis are key to understand complex physics and resolving critical failure modes. Analysts spend a considerable amount of time analyzing results and provide directions, design changes and recommendations. There is a scope to utilize advanced features of VR, AR and MR in CFD post process to find out the root cause of any failures occurred with

Savitha, Bhuduri, Sharma, Sachin

Transformative Deep Learning for Image Colorization with Machine Learning-Based Classification

2025-28-0317

11/06/2025

Imagine a user opening a technical manual, eager to troubleshoot an issue, only to find a mix of stark black-and-white illustrations alongside a few color images. This inconsistency not only detracts from the user experience but also complicates understanding. For technicians relying on these documents, grayscale graphics hinder quick interpretation of diagrams, extending diagnostics time and impacting overall productivity. Producing high-quality color graphics typically requires significant investment in time and resources, often necessitating a dedicated graphics team. Our innovative pipeline addresses this challenge by automating the colorization and classification of colored graphics. This approach delivers consistent, visually engaging content without the extensive investment in specialized teams, enhancing the visual appeal of materials and streamlining the diagnostic process for technicians. With clearer, more vibrant graphics, technicians can complete tasks more efficiently

Khalid, Maaz, Akarte, Anurag, Kale, Aniket, Rajmane, Gayatri, Nalawade, Komal

Eyes of Robot Operating System for Future Hands

2025-28-0246

11/06/2025

This paper presents a novel approach to automated robot programming and robot integration in manufacturing domain and minimizing the dependency on manual online/offline programming. Traditional industrial robots programming is typically done by online programing via teach pendants or by offline programming tools. This presents a major challenge as it requires skilled professionals and is a time-consuming process. In today’s competitive market, factories need to harness their full potential through smart and adaptive thinking to keep pace with evolving technology, customer demand, and manufacturing processes. This requires ability to manufacture multiple products on the same production line, minimum time for changeovers and implement robotic automation for efficiency enhancement. But each custom automation piece also demands significant human efforts for development and maintenance. By integrating the Robot Operating System (ROS) with vision-based 3D model generation systems, we address

Hepat, Abhijeet

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