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25th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2022

作者： Wzorek, Piotr Kryjak, Tomasz Embedded Vision Systems Group Agh University of Science and Technology Computer Vision Laboratory Department of Automatic Control and Robotics Kraków Poland Silesian University of Technology Department of Digital Systems Gliwice Poland

ISBN: (数字)9788362065424

ISBN: (纸本)9788362065424

In recent years, event cameras (DVS - Dynamic Vision Sensors) have been used in vision systems as an alternative or supplement to traditional cameras. They are characterised by high dynamic range, high temporal resolution, low latency, and reliable performance in limited lighting conditions - parameters that are particularly important in the context of advanced driver assistance systems (ADAS) and self-driving cars. In this work, we test whether these rather novel sensors can be applied to the popular task of traffic sign detection. To this end, we analyse different representations of the event data: event frame, event frequency, and the exponentially decaying time surface, and apply video frame reconstruction using a deep neural network called FireNet. We use the deep convolutional neural network YOLOv4 as a detector. For particular representations, we obtain a detection accuracy in the range of 86.9-88.9% mAP@0.5. The use of a fusion of the considered representations allows us to obtain a detector with higher accuracy of 89.9% mAP@0.5. In comparison, the detector for the frames reconstructed with FireNet is characterised by an accuracy of 72.67% mAP@0.5. The results obtained illustrate the potential of event cameras in automotive applications, either as standalone sensors or in close cooperation with typical frame-based cameras. © 2022 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Cameras

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Path Planning with Potential Field-Based Obstacle Avoidance in a 3D Environment by an Unmanned Aerial Vehicle

arXiv

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arXiv 2023年

作者： Batinovic, Ana Goricanec, Jurica Markovic, Lovro Bogdan, Stjepan University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Unska 3 Zagreb10000 Croatia

In this paper we address the problem of path planning in an unknown environment with an aerial robot. The main goal is to safely follow the planned trajectory by avoiding obstacles. The proposed approach is suitable for aerial vehicles equipped with 3D sensors, such as LiDARs. It performs obstacle avoidance in real time and on an on-board computer. We present a novel algorithm based on the conventional Artificial Potential Field (APF) that corrects the planned trajectory to avoid obstacles. To this end, our modified algorithm uses a rotation-based component to avoid local minima. The smooth trajectory following, achieved with the MPC tracker, allows us to quickly change and re-plan the UAV trajectory. Comparative experiments in simulation have shown that our approach solves local minima problems in trajectory planning and generates more efficient paths to avoid potential collisions with static obstacles compared to the original APF method. © 2023, CC BY-SA.

关键词： Motion planning

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Real-time FPGA implementation of the Semi-Global Matching stereo vision algorithm for a 4K/UHD video stream

arXiv

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arXiv 2023年

作者： Grabowski, Mariusz Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics Agh University of Science and Technology Krakow Poland

In this paper, we propose a real-time FPGA implementation of the Semi-Global Matching (SGM) stereo vision algorithm. The designed module supports a 4K/Ultra HD (3840 ×2160 pixels @ 30 frames per second) video stream in a 4 pixel per clock (ppc) format and a 64-pixel disparity range. The baseline SGM implementation had to be modified to process pixels in the 4ppc format and meet the timing constrains, however, our version provides results comparable to the original design. The solution has been positively evaluated on the Xilinx VC707 development board with a Virtex-7 FPGA device. © 2023, CC BY.

关键词： Field programmable gate arrays (FPGA)

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FROST: Fusion and Multimodal 3D Reconstruction of Icy Surfaces for Robotic Exploration

FROST: Fusion and Multimodal 3D Reconstruction of Icy Surfac...

引用

Computational Intelligence on Engineering/Cyber Physical Systems Companion (CIES Companion), IEEE Symposium on

作者： Huy Xuan Pham Erdal Kayacan Department of Electrical and Computer Engineering Artificial Intelligence in Robotics Laboratory (Air Lab) Aarhus University Aarhus C Denmark Automatic Control Group (RAT) Paderborn University Paderborn Germany

ISBN: (数字)9798331508494

ISBN: (纸本)9798331508500

Three-dimensional (3D) reconstruction serves as a cornerstone in various robotic applications, playing critical roles in scene understanding and navigation. Traditionally, LiDAR has been instrumental in generating precise point clouds of the environment, providing essential data for these applications. However, the efficacy of LiDAR sensors is significantly hindered in challenging conditions, such as the presence of water or icy surfaces. The complex interplay between laser beams and icy or non-ideal surfaces can result in signal degradation, distortion, or even complete signal loss, adversely affecting the accuracy and reliability of the 3D reconstruction process. The reflective and refractive properties of ice, along with its variable surface conditions, present challenges that traditional LiDAR sensors struggle to address. This paper proposes a diverse dataset to facilitate a multimodal approach for reconstructing icy surfaces using various sensors. A preliminary study based on this dataset demonstrates the feasibility of combining the geometric surface obtained from consecutive LiDAR scans with reconstructed meshes from visual cameras. The integration of distinct data sources has the potential to improve the robustness of reconstruction algorithms in diverse scenarios. The dataset can be downloaded at https://***/records/13862009.

关键词： Point cloud compression Surface reconstruction Laser radar Three-dimensional displays Navigation Ice Robustness Laser beams Image reconstruction Surface treatment

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Design and Validation of a Wireless Drone Docking Station

arXiv

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arXiv 2023年

作者： Stuhne, Dario Vasiljević, Goran Bogdan, Stjepan Kovačić, Zdenko LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb10000 Croatia

Drones are increasingly operating autonomously, and the need for extending drone power autonomy is rapidly increasing. One of the most promising solutions to extend drone power autonomy is the use of docking stations to support both landing and recharging of the drone. To this end, we introduce a novel wireless drone docking station with three commercial wireless charging modules. We have developed two independent units, both in mechanical and electrical aspects: the energy transmitting unit and the energy receiving unit. We have also studied the efficiency of wireless power transfer and demonstrated the advantages of connecting three receiver modules connected in series and parallel. We have achieved maximum output power of 96.5 W with a power transfer efficiency of 56.6% for the series connection of coils. Finally, we implemented the system in practice on a drone and tested both energy transfer and landing. Copyright © 2023, The Authors. All rights reserved.

关键词： Drones

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Human-Robot Pose Tracking Based on CNN with Color and Geometry Aggregation 16th

Human-Robot Pose Tracking Based on CNN with Color and Geo...

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16th International Conference on Social robotics, ICSR + InnoBiz 2024

作者： Xu, Yue Zhang, Yinlong Liu, Shuai Liu, Yuanhao Liang, Wei He, Hongsheng Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9789819611508

Accurately tracking the robotic arm and human joints is crucial to ensure safety during human-robot interaction. However, traditional pose tracking methods often exhibit insufficient performance and robustness in complex environments. The variations in the robotic arm’s environment and posture make it challenging for traditional methods to accurately capture the positions and posture of its joints. Specifically, when addressing challenges such as high similarity, occlusion, background complexity, and joint recognition failures, they often struggle to provide reliable and accurate results. To address these challenges, this paper proposes a human-robot pose tracking algorithm based on a new convolutional neural network model. To enhance detection accuracy, an improved color detection module is introduced to resolve joint misclassification. A geometric perception module is designed to accurately locate joints even under occlusion. Additionally, innovative iEMA and DBB modules are incorporated. The iEMA module employs edge detection technology to dynamically adjust thresholds for correct matching by improving the edge matching process. The DBB module refines the boundary box parameters for precise localization by introducing adaptive bounding box updates in real-time. This algorithm also integrates human pose recognition, enabling real-time pose recognition, thereby facilitating more intelligent and natural human-robot interaction. The algorithm has been rigorously evaluated on a custom-designed robotic arm platform. Experimental results validate the algorithm’s effectiveness and feasibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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Resilient Event-Triggered Model Predictive control for Adaptive Cruise control Under Sensor Attacks

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 807-809页

作者： Zhijian Hu Rong Su Kai Zhang Zeyuan Xu Renjie Ma School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technologyand the Center of Ultra-Precision Optoelectronic Instrument EngineeringHarbin Institute of TechnologyHarbin 150001China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585Singapore State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China IEEE

Dear Editor,This letter addresses the resilient model predictive control(MPC)problems for adaptive cruise control(ACC)systems under sensor *** the light of vulnerabilities of ACC systems to sensor attacks,an intrusion detection mechanism is proposed at the controller side to distinguish abnormal ***,the robust control gains are derived to design the terminal region constraint for MPC.

关键词： Trigger Event constraint

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Simulated Scattering of a Beam Carrying Orbital Angular Momentum from a Microparticle

Simulated Scattering of a Beam Carrying Orbital Angular Mome...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： McCarthy, John E. Avramov-Zamurovic, Svetlana Hart, Matthew B. Sivaprakasam, Vasanthi Weapons Robotics and Control Engineering Department United States Naval Academy 597McNair Rd AnnapolisMD21401 United States Optical Sciences Division United States Naval Research Laboratory 597McNair Rd AnnapolisMD21401 United States

ISBN: (纸本)9781957171258

We use multiphysics software COMSOL to simulate and evaluate interactions between structured light carrying orbital angular momentum and a single microparticles. We investigate the impact of particle location with respect to the structured light spatial intensity distribution. © Optica Publishing Group 2023 © 2023 The Author(s)

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Fuzzy controlled Adaptive Follow the Gap Obstacle Avoidance Algorithm 21

Fuzzy Controlled Adaptive Follow the Gap Obstacle Avoidance ...

引用

Proceedings of the 7th International Conference on robotics and Artificial Intelligence

作者： Bilal Yucel Abdurrahman Yilmaz Osman Ervan Hakan Temeltas Control and Automation Engineering Dept. Robotics Laboratory Istanbul Technical University Turkey

ISBN: (纸本)9781450385855

Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.

关键词： Mobile Robots Fuzzy control Path Planning Robot Navigation Adaptive control Obstacle Avoidance

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Interaction of a Beam Carrying Orbital Angular Momentum with an Ice Microparticle

Interaction of a Beam Carrying Orbital Angular Momentum with...

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2023 Propagation Through and Characterization of Atmospheric and Oceanic Phenomena, pcAOP 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Avramov-Zamurovic, Svetlana McCarthy, John E. Hart, Matthew B. Sivaprakasam, Vasanthi Weapons Robotics and Control Engineering Department United States Naval Academy 597 McNair Rd AnnapolisMD21401 United States Optical Sciences Division United States Naval Research Laboratory 4555 Overlook Ave. SW WashingtonDC20375 United States

We investigate the interaction of light carrying orbital angular momentum and a single ice microparticle using COMSOL multiphysics software. We report on the intensity and phase spatial distribution within the observa... 详细信息

ISBN: (纸本)9781957171289

关键词： Gaussian beams Light beams Light propagation Mueller matrices Orbital angular momentum multiplexing Structured light

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