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Overcoming the Fear of the Dark: Occlusion-Aware Model-Predictive Planning for Automated Vehicles Using Risk Fields

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arXiv 2023年

作者： van der Ploeg, Chris Nyberg, Truls Sánchez, José Manuel Gaspar Silvas, Emilia van de Wouw, Nathan Netherlands Organisation for Applied Scientific Research Integrated Vehicle Safety Group Helmond5700 AT Netherlands Eindhoven University of Technology Dynamics and Control Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands Eindhoven University of Technology Control Systems Technology Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands KTH Royal Institute of Technology Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science Stockholm100 44 Sweden Scania CV AB Södertälje151 87 Sweden

As vehicle automation advances, motion planning algorithms face escalating challenges in achieving safe and efficient navigation. Existing Advanced Driver Assistance Systems (ADAS) primarily focus on basic tasks, leaving unexpected scenarios for human intervention, which can be error-prone. Motion planning approaches for higher levels of automation in the state-of-the-art are primarily oriented toward the use of risk- or anti-collision constraints, using over-approximates of the shapes and sizes of other road users to prevent collisions. These methods however suffer from conservative behavior and the risk of infeasibility in high-risk initial conditions. In contrast, our work introduces a novel multi-objective trajectory generation approach. We propose an innovative method for constructing risk fields that accommodates diverse entity shapes and sizes, which allows us to also account for the presence of potentially occluded objects. This methodology is integrated into an occlusion-aware trajectory generator, enabling dynamic and safe maneuvering through intricate environments while anticipating (potentially hidden) road users and traveling along the infrastructure toward a specific goal. Through theoretical underpinnings and simulations, we validate the effectiveness of our approach. This paper bridges crucial gaps in motion planning for automated vehicles, offering a pathway toward safer and more adaptable autonomous navigation in complex urban contexts. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

Stabilization with Zero Location Constraints for Delay-Based Non-collocated Vibration Suppression ⁎

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IFAC-PapersOnLine 2021年第18期54卷 121-126页

作者： Haik Silm Wim Michiels Tomáš Vyhlídal Departement of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

A generally applicable design of non-collocated vibration absorption by a delayed resonator is proposed. It is grounded in the direct assignment of imaginary axis zeros of the transfer function between the periodic disturbance force and the target. We show that these transmission zeros are characterized as eigenvalues of a delay differential-algebraic system. Furthermore, a stabilizing local controller is added to the setup in order to widen the range of admissible vibration frequencies. These design requirements are translated into an optimization problem of the spectral abscissa function subjected to zero location constraints. The presented approach and algorithm are validated by a simulation on a three body lumped mass-spring system.

关键词： Vibration control Delayed resonator Transmission zeros Stability Spectral method

Recent advances in data-driven methods for degradation modelling across applications

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arXiv 2025年

作者： Jarosz, Anna Zagorowska, Marta Baranowski, Jerzy AGH University of Krakow Dept. of Automatic Control & Robotics al. Mickiewicza 30 Krakow30-059 Poland NTNU Department of Engineering Cybernetics Trondheim7034 Norway

Understanding degradation is crucial for ensuring the longevity and performance of materials, systems, and organisms. To illustrate the similarities across applications, this article provides a review of data-based method in materials science, engineering, and medicine. The methods analyzed in this paper include regression analysis, factor analysis, cluster analysis, Markov Chain Monte Carlo, Bayesian statistics, hidden Markov models, nonparametric Bayesian modeling of time series, supervised learning, and deep learning. The review provides an overview of degradation models, referencing books and methods, and includes detailed tables highlighting the applications and insights offered in medicine, power engineering, and material science. It also discusses the classification of methods, emphasizing statistical inference, dynamic prediction, machine learning, and hybrid modeling techniques. Overall, this review enhances understanding of degradation modelling across diverse domains. © 2025, CC BY-SA.

关键词： Hybrid materials

Modelling mobile robot navigation in 3D environments: camera-based stairs recognition in Gazebo

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Modelling mobile robot navigation in 3D environments: camera...

Moscow Workshop on Electronic and Networking Technologies (MWENT)

作者： Maksim Mustafin Tatyana Tsoy Edgar A. Martí nez-Garcí a Roman Meshcheryakov Evgeni Magid Intelligent Robotics Department Kazan Federal University Kazan Russia Industrial Engineering and Manufacturing Dept. Autonomous University of Ciudad Juarez Chihuahua Mexico Cyber-physical Lab V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia HSE University Moscow Russia

The task of sensory-based autonomous navigation of mobile robots requires data fusion from multiple sources in order to properly detect and recognize environmental obstacles. One of important issues mobile robots deal in a typical multi-level indoor environment is a stair well detection and negotiation. This paper presents ROS-based stairs detection implementation using onboard cameras of the Russian mobile crawler robot Servosila Engineer. Virtual experiments were performed in Gazebo environment with a single camera and a stereo camera.

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Keep off the grass: Permissible driving routes from radar with weak audio supervision

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arXiv 2020年

作者： Williams, David Martini, Daniele De Gadd, Matthew Marchegiani, Letizia Newman, Paul Oxford Robotics Institute Dept. Engineering Science University of Oxford Automation and Control Dept. Electronic Systems Aalborg University

Reliable outdoor deployment of mobile robots requires the robust identification of permissible driving routes in a given environment. The performance of LiDAR and vision-based perception systems deteriorates significantly if certain environmental factors are present e.g. rain, fog, darkness. Perception systems based on Frequency-Modulated Continuous Wave scanning radar maintain full performance regardless of environmental conditions and with a longer range than alternative sensors. Learning to segment a radar scan based on driveability in a fully supervised manner is not feasible as labelling each radar scan on a bin-by-bin basis is both difficult and time-consuming to do by hand. We therefore weakly supervise the training of the radarbased classifier through an audio-based classifier that is able to predict the terrain type underneath the robot. By combining odometry, GPS and the terrain labels from the audio classifier, we are able to construct a terrain labelled trajectory of the robot in the environment which is then used to label the radar scans. Using a curriculum learning procedure, we then train a radar segmentation network to generalise beyond the initial labelling and to detect all permissible driving routes in the environment. Copyright © 2020, The Authors. All rights reserved.

关键词： Landforms

Sense-Assess-eXplain (SAX): Building trust in autonomous vehicles in challenging real-world driving scenarios

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arXiv 2020年

作者： Gadd, Matthew De Martini, Daniele Marchegiani, Letizia Newman, Paul Kunze, Lars Oxford Robotics Institute Dept. Engineering Science University of Oxford United Kingdom Automation and Control Dept. Electronic Systems Aalborg University

This paper discusses ongoing work in demonstrating research in mobile autonomy in challenging driving scenarios. In our approach, we address fundamental technical issues to overcome critical barriers to assurance and regulation for largescale deployments of autonomous systems. To this end, we present how we build robots that (1) can robustly sense and interpret their environment using traditional as well as unconventional sensors;(2) can assess their own capabilities;and (3), vitally in the purpose of assurance and trust, can provide causal explanations of their interpretations and assessments. As it is essential that robots are safe and trusted, we design, develop, and demonstrate fundamental technologies in real-world applications to overcome critical barriers which impede the current deployment of robots in economically and socially important areas. Finally, we describe ongoing work in the collection of an unusual, rare, and highly valuable dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Autonomous vehicles

Improved Template Matching Based Stereo Vision Sparse 3D Reconstruction Algorithm

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Improved Template Matching Based Stereo Vision Sparse 3D Rec...

Chinese control and Decision Conference, CCDC

作者： Zhiyuan Liu Bin Song Yanning Guo Hang Xu Dept. of Control Science and Engineering Harbin Institute of Technology Harbin Aerospace System Engineering Shanghai Shanghai Engieering Research Center of Space Robotics Shanghai

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Stereo vision 3D reconstruction using keypoints matching methods can bring up problems, such as uneven distribution of points, or even mismatches. To solve the problems, we proposed a novel stereo vision 3D reconstruction algorithm based on template matching. First, considering that the similarity between left and right image of binocular camera can be high, template matching can be brought in to minify the searching range of every keypoint, thus enhance the accuracy of matches and make the reconstruction result more complete. The specific process of the proposed method includes the following steps: templates extraction, keypoint density index calculation, template matching, keypoint matching within template matched areas, point cloud generation, and point cloud stitching. Furthermore, a simulation environment was built up in Gazebo, and 3D reconstruction was carried out using the proposed method. Comparison experiment was carried out using brute force keypoint matching method and FLANN. Simulation results showed that the proposed method performed better and improved in both utilization of keypoints and reconstruction result.

关键词： Three-dimensional displays Cameras Stereo vision Mathematical model Indexes Solid modeling Image reconstruction

Distributed search of swarm robots using tree structure in unknown environment

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Transactions of the Korean Institute of Electrical Engineers 2018年第2期67卷 285-292页

作者： Lee, Gi Su Joo, Young Hoon Dept. of Control and Robotics Engineering Kunsan National University Korea Republic of

In this paper, we propose a distributed search of a cluster robot using tree structure in an unknown environment. In the proposed method, the cluster robot divides the unknown environment into 4 regions by using the LRF (Laser Range Finder) sensor information and divides the maximum detection distance into 4 regions, and detects feature points of the obstacle. Also, we define the detected feature points as Voronoi Generators of the Voronoi Diagram and apply the Voronoi diagram. The Voronoi Space, the Voronoi Partition, and the Voronoi Vertex, components of Voronoi, are created. The generated Voronoi partition is the path of the robot. Voronoi vertices are defined as each node and consist of the proposed tree structure. The root of the tree is the starting point, and the node with the least significant bit and no children is the target point. Finally, we demonstrate the superiority of the proposed method through several simulations. Copyright © The Korean Institute of Electrical Engineers.

关键词： Robots

Recognition and tracking of moving objects using label-merge method based on fuzzy clustering algorithm

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Transactions of the Korean Institute of Electrical Engineers 2018年第2期67卷 293-300页

作者： Lee, Seong Min Seong, Il Joo, Young Hoon Dept. of Control and Robotics Engineering Kunsan National University Korea Republic of

We propose a moving object extraction and tracking method for improvement of animal identification and tracking technology. First, we propose a method of merging separated moving objects into a moving object by using FCM (Fuzzy C-Means) clustering algorithm to solve the problem of moving object loss caused by moving object extraction process. In addition, we propose a method of extracting data from a moving object and a method of counting moving objects to determine the number of clusters in order to satisfy the conditions for performing FCM clustering algorithm. Then, we propose a method to continuously track merged moving objects. In the proposed method, color histograms are extracted from feature information of each moving object, and the histograms are continuously accumulated so as not to react sensitively to noise or changes, and the average is obtained and stored. Thereafter, when a plurality of moving objects are overlapped and separated, the stored color histogram is compared with each other to correctly recognize each moving object. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments. Copyright © The Korean Institute of Electrical Engineers

关键词： Object recognition