Browse Topic: Navigation and guidance systems

Items (1,092)

Predictive Steering Angle Generation Algorithm for High Efficiency Vehicle’s Path Optimization

2025-01-8791

04/01/2025

Predictive performance simulation of a high-efficiency lightweight vehicle is performed through development of a multi-physics MATLAB Simulink model including advanced vehicle dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its dimensions, slope, banking, and adhesion coefficient along the model space, elaborated from the track GPS data points. The vehicle’s reference trajectory is not priorly provided to the model at the simulation start as, during run-time, a predictive Steering Angle Generation (SAG) algorithm based on Nonlinear Model Predictive Control (NMPC) computes the optimal steering angle input needed to drive the vehicle on the track within its limits. Computation is based on fast predictive simulations of a simplified version of dynamics modelling of the vehicle. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the actual

De Carlo, Matteo, Manzone, Simone, de Carvalho Pinheiro, Henrique, Carello, Massimiliana

FIT File Processing for Accident Reconstruction

2025-01-8696

04/01/2025

It is becoming increasingly common for bicyclists to record their rides using specialized bicycle computers and watches, the majority of which save the data they collect using the Flexible and Interoperable Data Transfer (.fit) Protocol. The contents of .fit files are stored in binary and thus not readily accessible to users, so the purpose of this paper is to demonstrate the differences induced by several common methods of analyzing .fit files. We used a Garmin Edge 830 bicycle computer with and without a wireless wheel speed sensor to record naturalistic ride data at 1 Hz. The .fit files were downloaded directly from the computer, uploaded to the chosen test platforms - Strava, Garmin Connect, and GoldenCheetah - and then exported to .gpx, .tcx and .csv formats. Those same .fit files were also parsed directly to .csv using the Garmin FIT Software Developer Kit (SDK) FitCSVTool utility. The data in those .csv files (henceforth referred to as “SDK data”) were then either directly

Sweet, David, Bretting, Gerald

RGB2BEV-Net: A PyTorch-Based End-to-End Pipeline for RGB to BEV Segmentation Using an Extended Dataset for Autonomous Driving

2025-01-8023

04/01/2025

In this study, we introduce RGB2BEV-Net, an end-to-end pipeline that extends traditional BEV segmentation models by utilizing raw RGB images with Bird’s Eye View (BEV) generation. While previous work primarily focused on pre-segmented images to generate corresponding BEV maps, our approach expands this by collecting RGB images alongside their affiliated segmentation masks and BEV representations. This enables direct input of RGB camera sensors into the pipeline, reflecting real-world autonomous driving scenarios where RGB cameras are commonly used as sensors, rather than relying on pre-segmented images. Our model processes four RGB images through a segmentation layer before converting them into a segmented BEV, implemented in the PyTorch framework after being adapted from an original implementation that utilized a different framework. This adaptation was necessary to improve compatibility and ensure better integration of the entire system within autonomous vehicle applications. We

Hossain, Sabir, Lin, Xianke

A Motion-Aware Continuous Time LiDAR-Inertial SLAM Framework

2025-01-8044

04/01/2025

Towards the goal of real-time navigation of autonomous robots, the Iterative Closest Point (ICP) based LiDAR odometry methods are a favorable class of Simultaneous Localization and Mapping (SLAM) algorithms for their robustness under any light conditions. However, even with the recent methods, the traditional SLAM challenges persist, where odometry drifts under adversarial conditions such as featureless or dynamic environments, as well as high motion of the robots. In this paper, we present a motion-aware continuous-time LiDAR-inertial SLAM framework. We introduce an efficient EKF-ICP sensor fusion solution by loosely coupling poses from the continuous time ICP and IMU data, designed to improve convergence speed and robustness over existing methods while incorporating a sophisticated motion constraint to maintain accurate localization during rapid motion changes. Our framework is evaluated on the KITTI datasets and artificially motion-induced dataset sequences, demonstrating

Kokenoz, Cigdem, Shaik, Toukheer, Sharma, Abhishek, Pisu, Pierluigi, Li, Bing

Systematic Predictive Energy Management Algorithm Testing in MIL/SIL with Realistic Traffic Simulation

2025-01-8583

04/01/2025

Energy management strategy is essential for HEV’s to achieve an optimum of energy consumption. With predictive energy management, taking future vehicle speed predicted from ADAS map information, in-vehicle navigation traffic flow status information, and current speed into account, one could anticipate a considerable improvement in energy-saving. The major validating approach widely adopted for energy management algorithms nowadays is real-world vehicle testing, of which the economic and time costs are relatively high. Moreover, with advanced algorithms featuring AI coming into light, putting forward higher requirement in the richness of test cases, the drawback in coverage of vehicle testing is revealed. This paper proposed a MIL/SIL testing approach for predictive energy management algorithms, providing a partial replacement to, and overcome the limitations of, vehicle testing. In the testing setup, random traffic generated by MATLAB® based on real-time traffic condition will be taken

Yan, Yue, Ma, Xiudan, Wei, Xinli, Xiong, Jie, Deng, Yunfei

Dynamic Driving Task Assessment Scores for Scenarios Navigated by an OEM ADS-Equipped Vehicle

2025-01-8672

04/01/2025

One of the major issues facing the automated driving system (ADS)-equipped vehicle (AV) industry is how to evaluate the performance of an AV as it navigates a given scenario. The development and validation of a sound, consistent, and transparent dynamic driving task (DDT) assessment (DA) methodology is a key component of the safety case framework (SCF) of the Automated Vehicle – Test and Evaluation Process (AV-TEP) Mission, a collaboration between Science Foundation Arizona and Arizona State University. The DA methodology was presented in earlier work and includes the DA metrics from the recently published SAE J3237 Recommended Practice. This work extends and implements the methodology with an AV developed by OEM May Mobility in four diverse, real-world scenarios: (1) an oncoming vehicle entering the AV’s lane, (2) vulnerable road user (VRU) crossing in front of the AV’s path, (3) a vehicle executing a three-point turn encroaches into the AV’s path, and (4) the AV exhibiting aggressive

Wishart, Jeffrey, Rahimi, Shujauddin, Swaminathan, Sunder, Zhao, Junfeng, Frantz, Matt, Singh, Satvir, Como, Steven Gerard

Validation of SynthEyes for Use in Collision Reconstruction

2025-01-8688

04/01/2025

Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the

Perera, Nishan, Griffiths, Harrison, Prentice, Greg

Aggressive Autonomous Control on Snow and Ice

2025-01-8040

04/01/2025

In cold and snowy areas, low-friction and non-uniform road surfaces make vehicle control complex. Manually driving a car becomes a labor-intensive process with higher risks. To explore the upper limits of vehicle motion on snow and ice, we use an existing aggressive autonomous algorithm as a testing tool. We built our 1:5 scaled test platform and proposed an RGBA-based cost map generation method to generate cost maps from either recorded GPS waypoints or manually designed waypoints. From the test results, the AutoRally software can be used on our test platform, which has the same wheelbase but different weights and actuators. Due to the different platforms, the maximum speed that the vehicle can reach is reduced by 1.38% and 2.26% at 6.0 m/s and 8.5 m/s target speeds. When tested on snow and ice surfaces, compared to the max speed on dirt (7.51 m/s), the maximum speed decreased by 48% and 53.9%, respectively. In addition to the significant performance degradation on snow and ice, the

Yang, Yiming, Bos, Jeremy P.

Hierarchical Feature-Based Localization Using Scene Graphs in Off-Road Navigation

2025-01-8046

04/01/2025

While numerous advancements have been made in autonomous navigation for structured indoor and outdoor environments, these solutions often do not generalize well to off-road settings. There are unique challenges in such settings such as unreliable GPS, limited computational and memory resources, and sparse environmental features, making navigation particularly difficult. In our work, we propose a novel data structure called Hierarchical Dynamic Scene Graphs (HDSG) to address these challenges. HDSG captures environmental information at different resolutions, integrating both geometric and semantic features. It enables various navigation tasks such as localization, loop closure, and human interaction through the visualization of environmental features for remote operators. We evaluated the performance of localizing a robot’s position within the world frame by comparing compact spatial descriptors extracted from semi-consecutive scene graphs, derived from 3D LiDAR point clouds. Compared to

Alam, Fardifa Fathmiul, Luricich, Federico, Li, Nianyi, Jia, Yunyi, Li, Bing

Efficient Sidewalk Route Planning on Aerial Images with Cost-Based A* and Mini-Max Objective Function

2025-01-8032

04/01/2025

With the growing diversification of modern urban transportation options, such as delivery robots, patrol robots, service robots, E-bikes, and E-scooters, sidewalks have gained newfound importance as critical features of High-Definition (HD) Maps. Since these emerging modes of transportation are designed to operate on sidewalks to ensure public safety, there is an urgent need for efficient and optimal sidewalk routing plans for autonomous driving systems. This paper proposed a sidewalk route planning method using a cost-based A* algorithm and a mini-max-based objective function for optimal routes. The proposed cost-based A* route planning algorithm can generate different routes based on the costs of different terrains (sidewalks and crosswalks), and the objective function can produce an efficient route for different routing scenarios or preferences while considering both travelling distance and safety levels. This paper’s work is meant to fill the gap in efficient route planning for

Bao, Zhibin, Lang, Haoxiang, Lin, Xianke

Quantifying the Uncertainty in Bicycle-Computer Speed Measurements

2025-01-8701

04/01/2025

Bicycle computers record and store kinematic and physiologic data that can be useful for forensic investigations of crashes. The utility of speed data from bicycle computers depends on the accurate synchronization of the speed data with either the recorded time or position, and the accuracy of the reported speed. The primary goals of this study were to quantify the temporal asynchrony and the error amplitudes in speed measurements recorded by a common bicycle computer over a wide area and over a long period. We acquired 96 hours of data at 1-second intervals simultaneously from three Garmin Edge 530 computers mounted to the same bicycle during road cycling in rural and urban environments. Each computer recorded speed data using a different method: two units were paired to two different external speed sensors and a third unit was not paired to any remote sensors and calculated its speed based on GPS data. We synchronized the units based on the speed signals and used one of the paired

Booth, Gabrielle R., Siegmund, Gunter P.

A Review of Off-Road Datasets, Sensor Technologies and Terrain Traversability Analysis

2025-01-8339

04/01/2025

Autonomous ground navigation has advanced significantly in urban and structured environments, supported by the availability of comprehensive datasets. However, navigating complex and off-road terrains remains challenging due to limited datasets, diverse terrain types, adverse environmental conditions, and sensor limitations affecting vehicle perception. This study presents a comprehensive review of off-road datasets, integrating their applications with sensor technologies and terrain traversability analysis methods. It identifies critical gaps, including class imbalances, sensor performance under adverse conditions, and limitations in existing traversability estimation approaches. Key contributions include a novel classification of off-road datasets based on annotation methods, providing insights into scalability and applicability across diverse terrains. The study also evaluates sensor technologies under adverse conditions and proposes strategies for incorporating event-based and

Musau, Hannah, Ruganuza, Denis, Indah, Debbie, Mukwaya, Arthur, Gyimah, Nana Kankam, Patil, Ashish, Bhosale, Mayuresh, Gupta, Prakhar, Mwakalonge, Judith, Jia, Yunyi, Mikulski, Dariusz, Grabowsky, David, Hong, Jae Dong, Siuhi, Saidi

Prognostic Techniques in Automated Driving System (ADS) Vehicle Safety

2025-01-8094

04/01/2025

The recent advancements in fields such as sensors, AI, and IoT are majorly impacting the automotive industry. Automated Driving Systems (ADS) are developing rapidly, meaning that SAE J3016 Level 3 and above vehicles are quickly becoming a reality. As a result, maintenance of such systems becomes essential to ensure their safe and efficient operation. Prognostic techniques in particular are crucial to monitor the state of health and predicting the end of life for components. Prognostics engineering is being applied in many industries and for conventional automotive applications, but ADS is new technology, and the prognostics for these systems are still being developed and adapted. In this paper, we first present a review of the most used prognostic techniques across different safety-critical domains such as aerospace, power, and manufacturing. Then, we summarize the main challenges that must be faced to successfully develop novel approaches for prognostics of ADS components and provide

Merola, Francesco, Hanif, Athar, Lami, Giuseppe, Ahmed, Qadeer, Monohon, Mark

An Enhanced Approach for Improving Waterborne Positioning Accuracy Utilizing Multi-Epoch Elevation Constraints in Mobile RTK

2025-01-7156

03/19/2025

The rapid advancement of inland waterway transport has led to safety concerns, while real-time high-precision positioning in maritime contexts is essential for enhancing navigation efficiency and safety. To tackle this problem, this paper proposes a method for enhancing the accuracy of maritime Real - Time Kinematic (RTK) positioning using smartphones based on multi-epoch elevation constraints. Firstly, the elevation characteristics of smartphones in a maritime context were analyzed. Subsequently, exploiting the feature of gradual elevation variations when vessels navigate inland rivers, an appropriate sliding window was established to construct elevation constraint values, which were then integrated into the observation equations for filtering computations to boost positioning accuracy. Finally, synchronous observations were carried out using smartphones and geodetic receivers to compare and analyze the positioning accuracy before and after the addition of the elevation constraints

Wumaier, Diliyaer, Yu, Xianwen, Mu, Hongbo

Traffic Event Extraction and Geographization from Natural Language Web Text

2025-01-7213

03/19/2025

Real-time traffic event information is essential for various applications, including travel service improvement, vehicle map updating, and road management decision optimization. With the rapid advancement of Internet, text published from network platforms has become a crucial data source for urban road traffic events due to its strong real-time performance and wide space-time coverage and low acquisition cost. Due to the complexity of massive, multi-source web text and the diversity of spatial scenes in traffic events, current methods are insufficient for accurately and comprehensively extracting and geographizing traffic events in a multi-dimensional, fine-grained manner, resulting in this information cannot be fully and efficiently utilized. Therefore, in this study, we proposed a “data preparation - event extraction - event geographization” framework focused on traffic events, integrating geospatial information to achieve efficient text extraction and spatial representation. First

Hu, Chenyu, Wu, Hangbin, Wei, Chaoxu, Chen, Qianqian, Yue, Han, Huang, Wei, Liu, Chun, Fu, Ting, Wang, Junhua

A Method for Constructing Software and Hardware of a Multi-Source Fusion Intelligent Driving

2025-01-7158

03/19/2025

To meet the requirements of high-precision and stable positioning for autonomous driving vehicles in complex urban environments, this paper designs and develops a multi-sensor fusion intelligent driving hardware and software system based on BDS, IMU, and LiDAR. This system aims to fill the current gap in hardware platform construction and practical verification within multi-sensor fusion technology. Although multi-sensor fusion positioning algorithms have made significant progress in recent years, their application and validation on real hardware platforms remain limited. To address this issue, the system integrates BDS dual antennas, IMU, and LiDAR sensors, enhancing signal reception stability through an optimized layout design and improving hardware structure to accommodate real-time data acquisition and processing in complex environments. The system’s software design is based on factor graph optimization algorithms, which use the global positioning data provided by BDS to constrain

Zhan, KaiDi, Gao, Chengfa, Xu, Dawei, Lan, Minyi, Ding, Rongjing

Research on Triple-Frequency Dual-Ionosphere-Free Combination PPP Based on PPP-B2b Service

2025-01-7157

02/21/2025

The recent public release of the PPP-B2b service, along with advancements in multi-frequency and multi-GNSS systems, has opened up significant new opportunities for the development of Precise Point Positioning (PPP) technology. Utilizing the precise orbit and clock corrections provided by PPP-B2b and the increasing availability of multi-frequency signals, this paper introduces a novel tri-frequency, dual ionosphere-free PPP model based on PPP-B2b services. The model is designed with twelve unique tri-frequency combinations, tailored to various frequency choices, combination methodologies, and single/dual GNSS systems. Results from static positioning experiments indicate that the BDS-only tri-frequency dual ionosphere-free model offers substantial improvements over traditional models. Specifically, it achieves approximately a 25% increase in vertical accuracy and reduces convergence time by around 30% when compared to the BDS-only tri-frequency undifferenced uncombined model. This

Xu, Dawei, Gao, Chengfa, Xu, Zhenhao, Zhan, Kaidi, Guo, Songlin

Design of a Ship Path Planning Scheme Incorporating Wind and Current Effects with COLREGS Compliance

2025-01-7177

02/21/2025

Path planning algorithms are critical technologies for intelligent ship systems, as scientifically optimized paths enable safe navigation and efficient avoidance of waterborne obstacles. To address the limitations of current ship path planning models, which often fail to adequately consider the combined effects of wind, current, and the International Regulations for Preventing Collisions at Sea (COLREGS), this study proposes an enhanced path planning method. The method integrates environmental factors, such as wind and current, and COLREGS into an improved Artificial Potential Field(APF) framework. Specifically, the influence of wind and current is modeled as "environmental forces," while the navigation constraints imposed by COLREGS are transformed into virtual obstacles, generating corresponding repulsive forces to refine the algorithm. Simulation experiments conducted under both single-ship and multi-ship scenarios validate the feasibility and effectiveness of the proposed approach

Shangqing, Feng, Jinli, Xiao, Langxiong, Gan, Geng, Chen, Hui, Li, Guanliang, Zhou

Dynamic Evaluation Method for Public Transport Operation Indicators Based on Rank Transformation

2025-01-7219

02/21/2025

This study presents a method to evaluate the daily operation of traditional public transportation using multi-source data and rank transformation. In contrast with previous studies, we focuses on dynamic indicators generated during vehicle operation, while ignoring static indicators. This provides a better reference value for the daily operation management of public transport vehicles. Initially, we match on-board GPS data with network and stop coordinates to extract arrival and departure timetable. This helps us calculate dynamic operational metrics such as dwell time, arrival interval, and frequency of vehicle bunching and large interval. By integrating IC card data with arrival timetable, we can also estimate the number of people boarding at each stop and derive passenger arrival time, waiting time, and average waiting time. Finally, we developed a comprehensive dynamic evaluation method of public transportation performance, covering the three dimensions: bus stops, vehicles, and

Zhou, Yang, Shao, Yichang, Han, Zhongyi, Ye, Zhirui

Research on SINS/GNSS Integrated Positioning for Highway Vehicles

2025-01-7164

02/21/2025

This study investigates the application of integrated positioning based on SINS (Strapdown Inertial Navigation System) and GNSS (Global Navigation Satellite System) for highway vehicle navigation. While GNSS offers high-precision outdoor positioning, it is susceptible to signal obstructions, whereas SINS enables autonomous positioning without external signals but accumulates drift errors over time. To enhance positioning accuracy, this study employs three nonlinear filters—Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF)—for multi-source data fusion. Experimental results demonstrate that EKF, UKF, and CKF achieve faster convergence, higher stability, and smoother error curves when handling nonlinear problems. Through simulation experiments and field measurements, the strengths of each algorithm are validated across different metrics and directions. Considering sensor limitations and implementation complexity, EKF outperforms other algorithms

Zhang, Hongbin, Wen, Chengju, Liu, Zhe, Lin, Chen

Design of Smart Assistive Headgear for The Blind

2025-28-0096

02/07/2025

This paper presents the development of a cost-effective assistive headgear designed to address the navigation challenges faced by millions of visually impaired individuals in India. Existing solutions are often prohibitively expensive, leaving a significant portion of this population underserved. To address this gap, we propose a novel human-machine interface that utilizes a synergistic combination of computer vision, stereo imaging, and haptic feedback technologies. The focus of this project lies in the creation of a practical and affordable headgear that empowers visually impaired users with real time obstacle detection and navigation capabilities. The solution leverages computer vision for environmental analysis and integrates haptic feedback for intuitive user guidance. This paper details the design intricacies of the headgear, along with the implementation methodologies employed. We present comprehensive testing results and discuss the project's potential to significantly enhance

Manu, Rohith, S Nair, Sreeram, Biju, Mariya, KM, Devika, Sadique, Anwar

Aerospace & Defense Technology: February 2025

25AERP0202/06/2025

The Art of Reverse Engineering Yesteryear for Aerospace and Defense Data Storage Drives Manufacturing Spotlight: Machining Complex Parts and Materials for Space Flight and Exploration Notre Dame's New Boundary Breaking Mach 10 Quiet Wind Tunnel Shape-Shifting Antenna Poised to Transform Communications British Army Completes First Test of Drone Killing Radio Frequency Weapon A Swarm of Sensors, Rovers and Astronauts Explore the 'Moon' Researchers at the German Aerospace Center have developed a new approach to networked communications that could theoretically occur on the Moon or in environments on Earth where conventional communications are unavailable. Army Researchers Examine Nanotechnology for Climate Solutions Army scientists are joining forces with experts from across the nation to tackle the climate crisis using the power of nanotechnology Airman Brings Fuel Sampling Innovation to Eglin, Possibly Air Force The U.S. Air Force is testing a new prototype single point nozzle adapter

Adaptive Localization Algorithm for Autonomous Mining Trucks with Motion Distortion Removal

2025-01-7027

01/31/2025

During the operation of autonomous mining trucks in the process of crushing stones, the GPS signal is lost due to signal blockage by the crushing workshop. Simultaneous Localization and Mapping (SLAM) becomes critical for ensuring accurate vehicle positioning and smooth operation. However, the bumpy road conditions and the scarcity of plane and corner feature points in mining environments pose challenges to SLAM algorithms in practical applications, such as pose jumps and insufficient positioning accuracy. To address this, this paper proposes a high-precision positioning algorithm based on inertial navigation 3D signals, incorporating point cloud motion distortion correction, a vehicle roll model, and an Adaptive Kalman Filter (AKF). The goal is to improve the positioning accuracy and stability of autonomous mining trucks in complex scenarios. This paper utilizes real-world operational data from mining vehicles and adopts a 3D point cloud motion distortion correction algorithm to

Meng, Chunyang, Song, Kang, Xie, Hui, Xing, Wanyong

Simulation Analysis of Multi-Objective Functions in Mobile Robot Navigation Based on Enhanced Deep Q-Network Algorithm

2024-01-5110

12/24/2024

This research, path planning optimization of the deep Q-network (DQN) algorithm is enhanced through integration with the enhanced deep Q-network (EDQN) for mobile robot (MR) navigation in specific scenarios. This approach involves multiple objectives, such as minimizing path distance, energy consumption, and obstacle avoidance. The proposed algorithm has been adapted to operate MRs in both 10 × 10 and 15 × 15 grid-mapped environments, accommodating both static and dynamic settings. The main objective of the algorithm is to determine the most efficient, optimized path to the target destination. A learning-based MR was utilized to experimentally validate the EDQN methodology, confirming its effectiveness. For robot trajectory tasks, this research demonstrates that the EDQN approach enables collision avoidance, optimizes path efficiency, and achieves practical applicability. Training episodes were implemented over 3000 iterations. In comparison to traditional algorithms such as A*, GA

Arumugam, Vengatesan, Alagumalai, Vasudevan, Rajendran, Sundarakannan

Application of Servo-Assisted Technology in Commercial Vehicle Steering Systems for Autonomous Mobility in Off-Road Trucks. Case Study: Application on 8x2/8x4 Sugarcane Trucks

2024-36-0033

12/20/2024

The exponential growth of the agribusiness market in Brazil combined with the high receptivity among farmers of new technological solutions has driven the study and implementation of high technology in the field. This work aimed to apply servo-assisted driving technology to enable autonomous mobility in an off-road sugarcane truck responsible for harvesting sugarcane. The technology consists of a conventional hydraulic steering with a motor, ECU and torque and angle sensors responsible for reading input data converted from GPS signals and previously recorded tracking lines. The motor responsible for replacing 100% of the physical force generated by the driver acts in accordance with the required torque demand, and the sensors combined with the ECU correct the course to meet the follow-up line through external communication ports. The accuracy of the system depends exclusively on the accuracy of the GPS signal, in this case reaching 2,5 cm, which is considered extremely high accuracy

Oliveira Santos Neto, Antídio, Lara, Vanderlei, Silva, Everton, Destro, Daniel, Moura, Márcio, Borges, Felipe, Haegele, Timo

Artificial Intelligence in Aeronautical Systems: Taxonomy

AIR6987 (Current)

12/12/2024

The objective of this document is to provide a classification of AI techniques that may be used in AI-based systems for aeronautical products. Aeronautical products include products in Airborne and Air Traffic Management (ATM) and Air Navigation Systems (ANS) domains for crewed and uncrewed aircraft. This document is: Intended to provide an understanding of the AI space, which will improve over time Not intended to provide guidance, objectives, or safety considerations A scenario builder for AI technologies, in particular supervised learning The publication of a taxonomy document for the aviation domain is an opportunity to support other AI standardization initiatives that will also publish taxonomy documents. Disclaimer: This document provides content to support other products of the SAE G-34/EUROCAE WG-114 Committee.

G-34 Artificial Intelligence in Aviation

Autonomous Mobile Robot for Gas Leak Localization

2024-01-5226

12/10/2024

LIDAR-based autonomous mobile robots (AMRs) are gradually being used for gas detection in industries. They detect tiny changes in the composition of the environment in indoor areas that is too risky for humans, making it ideal for the detection of gases. This current work focusses on the basic aspect of gas detection and avoiding unwanted accidents in industrial sectors by using an AMR with LIDAR sensor capable of autonomous navigation and MQ2 a gas detection sensor for identifying the leakages including toxic and explosive gases, and can alert the necessary personnel in real-time by using simultaneous localization and mapping (SLAM) algorithm and gas distribution mapping (GDM). GDM in accordance with SLAM algorithm directs the robot towards the leakage point immediately thereby avoiding accidents. Raspberry Pi 4 is used for efficient data processing and hardware part accomplished with PGM45775 DC motor for movements with 2D LIDAR allowing 360° mapping. The adoption of LIDAR-based AMRs

Feroz Ali, L., Madhankumar, S., Hariush, V.C., Jahath Pranav, R., Jayadeep, J., Jeffrey, S.

Making a Material Difference in Aerospace & Defense Electronics

TBMG-52137

12/01/2024

Vision-Based Approach and Landing System (VALS)

TBMG-52194

12/01/2024

There are certain situations when landing an Advanced Air Mobility (AAM) aircraft is required to be performed without assistance from GPS data. For example, AAM aircraft flying in an urban environment with tall buildings and narrow canyons may affect the ability of the AAM aircraft to effectively use GPS to access a landing area. Incorporating a vision-based navigation method, NASA Ames has developed a novel Alternative Position, Navigation, and Timing (APNT) solution for AAM aircraft in environments where GPS is not available.

An ACO-Based Path Planning Algorithm for UAV in Urban Airspace

2024-01-7024

11/15/2024

Navigating Unmanned Aerial Vehicles (UAVs) in urban airspace poses significant challenges for fast and efficient path planning due to the environment's complexity and dynamism. However, the existing research on UAV path planning has ignored the speed of algorithmic convergence and the smoothness of the generated path, which are critical for adapting to the dynamic changing of the urban airspace as well as for the safety of ground personnel, and the UAV itself. In this study, we propose an enhanced Ant Colony Optimization (ACO) algorithm that incorporates two heuristic functions: the compass heuristic and the inertia heuristic. These functions guide the ant agents in their movement towards the destination, aiming for faster convergence and smoother trajectories. The algorithm is evaluated using a gray-scale lattice map generated from ground personnel risk data in Suzhou City. The results indicate that the improved ACO path planning algorithm demonstrates both efficiency and quality

Wang, Bofan, Zhao, Zhouye, Hu, Boya, Liu, Yufan, Ru, Xiaoyu, Tong, Ziyue, Jia, Qing

Multi-sensor Fusion-based Vehicle Localization

EPR2024023

10/21/2024

Multi-sensor fusion (MSF) is believed to be a promising tool for vehicular localization in urban environments. Due to the differences in principles and performance of various onboard vehicle sensors, MSF inevitably suffers from heterogeneous sources and vulnerability to cyber-attacks. Therefore, an essential requirement of MSF is the capability of providing a consumer-grade solution that operates in real-time, is accurate, and immune to abnormal conditions with guaranteed performance and quality of service for location-based applications. In other words, an MSF algorithm depends heavily on data synchronization, cost, an accurate process model, a prior knowledge of covariance matrices, integrity assessments, and security against cyber-attacks. Multi-sensor Fusion-based Vehicle Localization addresses trending technologies in MSF-based vehicle localization and outlines some insights into the unsettled issues and their potential solutions. The discussions and outlook are presented as a

Guo, Ge, Liu, Jiageng, Liu, Guangheng

A Comparative Study on Autonomous Vehicle Local Path Planning Through Model Predictive Control and Frenet Frame Method

12-07-04-0029

10/07/2024

In recent years, autonomous vehicles (AVs) have been receiving increasing attention from investors, automakers, and academia due to the envisioned potentials of AVs in enhancing safety, reducing emissions, and improving comfort. The crucial task in AV development boils down to perception and navigation. The research is underway, in both academia and industry, to improve AV’s perception and navigation and reduce the underlying computation and costs. This article proposes a model predictive control (MPC)-based local path-planning method in the Cartesian framework to overcome the long computation time and lack of smoothness of the Frenet method. A new equation is proposed in the MPC cost function to improve the safety in path planning. In this regard, an AV is built based on a 2015 Nissan Leaf S by modifying the drive-by-wire function and installing environment perception sensors and computation units. The custom-made AV then collected data in Norman, Oklahoma, and assisted in the

Arjmandzadeh, Ziba, Abbasi, Mohammad Hossein, Wang, Hanchen, Zhang, Jiangfeng, Xu , Bin

A Powerful Vision-Based Autonomy Alternative to LiDAR, Radar, GPS

TBMG-51747

10/01/2024

Southwest Research Institute has developed off-road autonomous driving tools with a focus on stealth for the military and agility for space and agriculture clients. The vision-based system pairs stereo cameras with novel algorithms, eliminating the need for LiDAR and active sensors.

RTK and Sensor Fusion for Autonomous Vehicle Navigation & Guidance

TBMG-51724

10/01/2024

New Technique Could Improve GPS Navigation Devices

TBMG-51746

10/01/2024

A new scientific technique could significantly improve the reference frames that millions of people rely upon each day when using GPS navigation services, according to a recently published article in Radio Science.

Efficient GPS Route Matching Method for Battery Electric Bus Fleets

2024-24-0026

09/18/2024

A challenge of public transportation GPS data is the frequent utilization of monitoring systems with low sampling rates, primarily driven by the high costs associated with cellular data transmission of large datasets. Altitude data is often imprecise or not recorded at all in regions without large elevation changes. The low data quality limits the use of the data for further detailed investigations like a realistic energy consumption forecast for assessing the electrical grid load resulting from charging the vehicle fleet. Modern research often reconstructs speed data only, or uses additional GPS loggers, which is associated with increased costs in the vehicle fleet. The importance of precise and high-quality altitude data and specialized expertise in mountainous regions are frequently overlooked. This paper introduces an efficient new route matching method to reconstruct speed and respective road slope data of a GPS signal sampled at low frequency for a public transportation electric

Hitz, Arne, Konzept, Anja, Reick, Benedikt, Rheinberger, Klaus

Aerospace & Defense Technology: September 2024

24AERP0909/05/2024

How Next-Generation Edge Computers Will Shape Drone Warfare Microchip's New Microprocessor to Enable Generational Leap in Spaceflight Computing How Aerospace Startups Can Seek Partnerships to Secure Their Future Quality Gearing Keeps Mission-Critical Systems Rotating for Combat This Laser Clock Could Transform Satellite Navigation Accuracy Everyday Life, Improved by Light: GRYPHON's Photonic Discoveries Engineers Develop More Accurate AI Algorithm for Improving Nuclear Reactor Performance Purdue University research reactor serves as test bed for optimizing performance of small modular reactors. Creating and Verifying Stable AI-Controlled Systems in a Rigorous, Flexible Way Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines. Will Generative AI Transform Robotics? In the current wave of excitement about applying large vision-language models and generative AI to robotics

Approach for Extrinsic Calibration of a Light Detection and Ranging Sensor and a Monocular Camera Using Bounding Boxes

2024-01-5092

09/04/2024

Sensor calibration plays an important role in determining overall navigation accuracy of an autonomous vehicle (AV). Calibrating the AV’s perception sensors, typically, involves placing a prominent object in a region visible to the sensors and then taking measurements to further analyses. The analysis involves developing a mathematical model that relates the AV’s perception sensors using the measurements taken of the prominent object. The calibration process has multiple steps that require high precision, which tend to be tedious and time-consuming. Worse, calibration has to be repeated to determine new extrinsic parameters whenever either one of the sensors move. Extrinsic calibration approaches for LiDAR and camera depend on objects or landmarks with distinct features, like hard edges or large planar faces that are easy to identify in measurements. The current work proposes a method for extrinsically calibrating a LiDAR and a forward-facing monocular camera using 3D and 2D bounding

Omwansa, Mark, Sharma, Sachin, Meyer, Richard, Brown, Nicholas

Everyday Life, Improved by Light: GRYPHON’s Photonic Discoveries

TBMG-51468

09/01/2024

Radio frequency (RF) and microwave signals are integral carriers of information for technology that enriches our everyday life – cellular communication, automotive radar sensors, and GPS navigation, among others. At the heart of each system is a single-frequency RF or microwave source, the stability and spectral purity of which is critical. While these sources are designed to generate a signal at a precise frequency, in practice the exact frequency is blurred by phase noise, arising from component imperfections and environmental sensitivity, that compromises ultimate system-level performance.

This Laser Clock Could Transform Satellite Navigation Accuracy

TBMG-51467

09/01/2024

Emergency Braking System: Verification of system behavior on commercial vehicles equipped with drum braking system

2024-36-0309

08/09/2024

In recent years, new technologies are being developed and applied to commercial vehicles. Such technologies support on development and implementation of new functions making these products safer, benefiting the society in general. One of the areas that can be mentioned is the vehicle safety. Among too many technologies, the emergency brake system is that one who came to support and assist drivers in critical situations that cannot be avoided. The Advanced Emergency Brake System, AEBS, consists of identifying other vehicles ahead, and, in case of detecting a risk of collision, automatically applies the service brakes to avoid accidents. The system works in situations when there is a sudden traffic stop, the vehicle is passing through intersections and when the driver distracts due to inappropriate use of mobile telephone devices. The aim of this work was to evaluate the emergency braking performance of a 6x4 tractor with a double semi-trailer, at flat asphalt. Both vehicles of

Dias, Eduardo Miranda, Rudek, Claudemir, Travaglia, Carlos Abflio Passos, Rodrigues, André, Brito, Danilo

To 6G and Beyond: Penn Engineers Unlock the Next Generation of Wireless Communications

24AERP08_07

08/01/2024

In the early 2010s, LightSquared, a multibillion-dollar startup promising to revolutionize cellular communications, declared bankruptcy. The company couldn't figure out how to prevent its signals from interfering with those of GPS systems. Now, Penn Engineers have developed a new tool that could prevent such problems from ever happening again: an adjustable filter that can successfully prevent interference, even in higher-frequency bands of the electromagnetic spectrum.

To 6G and Beyond: Penn Engineers Unlock the Next Generation of Wireless Communications

TBMG-51245

08/01/2024

In the early 2010s, LightSquared, a multibillion-dollar startup promising to revolutionize cellular communications, declared bankruptcy. The company couldn’t figure out how to prevent its signals from interfering with those of GPS systems.

Velocity Estimation of a Descending Spacecraft in Atmosphereless Environment Using Deep Learning

2024-26-0484

06/01/2024

Today’s space programs are ambitious and require increased level of onboard autonomy. Various sensing techniques and algorithms were developed over the years to achieve the same. However, vision-based sensing techniques have enabled higher level of autonomy in the navigation of space systems. The major advantage of vison-based sensing is its ability to offer high precision navigation. However, the traditional vision-based sensing techniques translate raw image into data which needs to be processed and can be used to control the spacecraft. The increasingly complex mission requirements motivate the use of vision-based techniques that use artificial intelligence with deep learning. Availability of sufficient onboard processing resources is a major challenge. Though space-based deployment of deep learning is in the experimental phase, but the space industry has already adopted AI on the ground systems. Deep learning technique for spacecraft navigation in an unknown and unpredictable

Avanashilingam, Jayanth Balaji, Thokala, Satish

Design and Manufacturing of an Inclinometer Sensing Element for Launch Vehicle Applications

2024-26-0419

06/01/2024

Indian Space Research Organisation (ISRO) uses indigenously developed launch vehicles like PSLV, GSLV, LVM3 and SSLV for placing remote sensing and communication satellites along with spacecrafts for other important scientific applications into earth bound orbits. Navigation systems present in the launch vehicle play a pivotal role in achieving the intended orbits for these spacecrafts. During the assembly of these navigation packages on the launch vehicle, it is required to measure the initial tilt of the navigation sensors for any misalignment corrections, which is given as input to the navigation software. A high precision inclinometer is required to measure these tilts with a resolution of 1 arc-second. In this regard, an indigenous inclinometer is being designed. The sensing element of this design comprises of a compliant mechanism which is designed to sense the tilt by measuring the displacement of a proof mass occurring due to the respective component of earth’s gravitational

Shaju, Tony M, Krishna, Nirmal, Rao, G Nagamalleswara, Kumar, T Suresh, K, Pradeep

Researchers Help Robots Navigate Efficiently in Uncertain Environments

24AERP05_07

05/01/2024

A new algorithm reduces travel time by identifying shortcuts a robot could take on the way to its destination. Massachusetts Institute of Technology, Cambridge, Massachusetts If a robot traveling to a destination has just two possible paths, it needs only to compare the routes' travel time and probability of success. But if the robot is traversing a complex environment with many possible paths, choosing the best route amid so much uncertainty can quickly become an intractable problem. MIT researchers developed a method that could help this robot efficiently reason about the best routes to its destination. They created an algorithm for constructing roadmaps of an uncertain environment that balances the tradeoff between roadmap quality and computational efficiency, enabling the robot to quickly find a traversable route that minimizes travel time.

Mapping out future vehicle cockpits

24AUTD05_09

05/01/2024

Game-like navigation visuals Conversational-style voice commands. Contactless biometric sensing. A tidal wave of software code and sensing technologies are being prepped to alter in-vehicle activities. Two supplier companies, TomTom and Mitsubishi Electric Automotive America (MEAA), recently presented their concept cockpit demonstrators to media at TomTom's North American corporate offices in Farmington Hills, Michigan. A few highlights:

Buchholz, Kami

Analysis of Error Mechanisms of Vibrating Gyroscopes Operating in a Slowly Changing Environment

2024-01-5044

04/17/2024

This study presents the constructed electromechanical model and the analysis of the obtained nonlinear systems. An algorithm for compensating the nonlinear drift of a gyroscope in a microelectromechanical system is proposed. Tests were carried out on a precision rotating base, with the angular velocity changing as per the program. Bench testing the gyroscope confirmed the results, which were also supported by the parameter calibration. The analytical method was further validated through experimental results, and a correction algorithm for the mathematical model was developed based on the test results. After calibration and adjusting the gyroscope’s systematic flaws, the disparity in calculating the precession angle was within 1/100th of an angular second over an interval of approximately 1000 s. Currently, research is underway on the new nonlinear dynamic characteristics of electrostatically controlled microstructures. The results of the integrated navigation system of small satellites

Trung Giap, Vu The

VISION: Vehicle Infrared Signature Aware Off-Road Navigation

2024-01-2661

04/09/2024

Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner. Vehicle

Lonari, Yashodeep, Naber, Jeffrey, Korivi, Vamshi, Tison, Nathan, Rynes, Peter, Yeefeng, Ruan

Design, Prototyping, and Implementation of a Vehicle-to-Infrastructure (V2I) System for Eco-Approach and Departure through Connected and Smart Corridors

2024-01-1982

04/09/2024

The advent of Vehicle-to-Everything (V2X) communication has revolutionized the automotive industry, particularly with the rise of Advanced Driver Assistance Systems (ADAS). V2X enables vehicles to communicate not only with each other (V2V) but also with infrastructure (V2I) and pedestrians (V2P), enhancing road safety and efficiency. ADAS, which includes features like adaptive cruise control and automatic intersection navigation, relies on V2X data exchange to make real-time decisions and improve driver assistance capabilities. Over the years, the progress of V2X technology has been marked by standardization efforts, increased deployment, and a growing ecosystem of connected vehicles, paving the way for safer and more efficient automated navigation. The EcoCAR Mobility Challenge was a 4-year student competition among 12 universities across the United States and Canada sponsored by the U.S. Department of Energy, MathWorks, and General Motors, where each team received a 2019 Chevrolet

Chowduri, Suhrit, Midlam-Mohler, Shawn, Singh, Karun Prateek

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