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arXiv 2023年

作者： Li, Kailai Cao, Ziyu Hanebeck, Uwe D. The Division of Automatic Control Department of Electrical Engineering Linköping University Sweden The Intelligent Sensor-Actuator-Systems Laboratory Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Germany

We introduce a novel framework of continuous-time ultra-wideband-inertial sensor fusion for online motion estimation. Quaternion-based cubic cumulative B-splines are exploited for parameterizing motion states continuously over time. Systematic derivations of analytic kinematic interpolations and spatial differentiations are further provided. Based thereon, a new sliding-window spline fitting scheme is established for asynchronous multi-sensor fusion and online calibration. We conduct a dedicated validation of the quaternion spline fitting method, and evaluate the proposed system, SFUISE (spline fusion-based ultra-wideband-inertial state estimation), in real-world scenarios using public data set and experiments. The proposed sensor fusion system is real-time capable and delivers superior performance over state-of-the-art discrete-time schemes. We release the source code and own experimental data at https://***/KIT-ISAS/SFUISE . Copyright © 2023, The Authors. All rights reserved.

关键词： Motion estimation

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Camera/LiDAR Sensor Fusion-based Autonomous Navigation

Camera/LiDAR Sensor Fusion-based Autonomous Navigation

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Abdullah Yusefi Akif Durdu Ibrahim Toy Department of Electrical and Electronics Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkey Research and Development MPG Machinery Production Group Inc. Co. Konya Turkey

This research presents a novel approach for autonomous navigation of Unmanned Ground Vehicles (UGV) using a camera and LiDAR sensor fusion system. The proposed method is designed to achieve a high rate of obstacle detection, distance estimation, and obstacle avoidance. In order to thoroughly study the form of things and decrease the problem of object occlusion, which frequently happens in camera-based object recognition, the 3D point cloud received from the LiDAR depth sensors is used. The proposed camera and LiDAR sensor fusion design balance the benefits and drawbacks of the two sensors to produce a detection system that is more reliable than others. The UGV's autonomous navigation system is then provided with the region proposal to re-plan its route and navigate appropriately. The experiments were conducted on a UGV system with high obstacle avoidance and fully autonomous navigation capabilities. The outcomes demonstrate that the suggested technique can successfully maneuver the UGV and detect impediments in actual situations.

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Fault Tolerant Dynamic Task Assignment for UAV-based Search Teams

arXiv

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arXiv 2024年

作者： Nasir, Ali AlDurgam, Mohammad Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics KFUPM Dhahran Saudi Arabia Industrial and Systems Engineering Department KFUPM Dhahran Saudi Arabia

This research offers a novel framework for dynamic task assignment for unmanned aerial vehicles (UAVs) in cooperative search settings. Notably, it incorporates post-fault UAV capabilities into job assignment techniques, assuring operational dependability in the event of sensor and actuator failures. A significant innovation is the utilization of UAV battery charge to assess range relative to search objectives, hence improving job distribution while conserving battery life. This model integrates repair, recharge, and stochastic goal recurrence, hence increasing its real-world applicability. Using stochastic dynamic programming, this method makes it simpler to determine optimal assignment policies offline so they may be implemented rapidly online. This paper emphasizes the holistic aspect of the proposed model, which connects high-level task rules to low-level control capabilities. A simulation-based case study proves its usefulness, highlighting its robustness in fault-prone and battery-variable settings. Overall, this paper proposes and demonstrates a comprehensive method for assigning UAV tasks that integrates defect awareness, battery management, and multilayer control through the use of stochastic dynamic programming. © 2024, CC BY.

关键词： Stochastic systems

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A Review on Collaborative Robots in Industrial and Service Sectors

A Review on Collaborative Robots in Industrial and Service S...

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2022 International Siberian Conference on control and Communications, SIBCON 2022

作者： Sultanov, Ramir Sulaiman, Shifa Li, Hongbing Meshcheryakov, Roman Magid, Evgeni Kazan Federal University Intelligent Robotics Department Kazan Russia Shanghai Jiao Tong University Department of Instrument Science and Engineering Shanghai China V. A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences Cyber-physical Lab Moscow Russia HSE University Moscow Russia

ISBN: (纸本)9781665476287

Today, a collaborative robotics is a rapidly developing area due to its applications in a broad variety of sectors. Collaborative robots (cobots) are robots, which are designed specifically to work along with humans in a common workspace. This article discusses modern cobots employed in industrial and service sectors. Research activities associated with cobots used in virtual environments and real world experiments are described. The ISO/TS 15066:2016 technical specifications followed by cobots for ensuring safety to human operators are emphasized. © 2022 IEEE.

关键词： ISO Standards

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SLAM-Based Joint Calibration of Differential RSS Sensor Array and Source Localization 49

SLAM-Based Joint Calibration of Differential RSS Sensor Arra...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Fu, Linya Qiao, Xu Huang, Shoudong Mao, Guoqiang Lin, Zhiyun Li, Youfu Kong, He Robotics Institute Uni. of Technology Sydney Sydney Australia Xidian University State Key Laboratory of Integrated Services Networks China City University of Hong Kong Department of Mechanical Engineering China Southern Uni. of Sci. and Tech. Shenzhen Key Laboratory of Control Theory and Intelligent Systems Shenzhen China Southern Uni. of Sci. and Tech. Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China

ISBN: (纸本)9798350331820

Sensor arrays generating differential received signal strength (DRSS) measurements have found many applications in robotics. However, accurate calibration of these sensor arrays remains a challenge. Most existing methods are impractical in that they assume to know signal source positions or certain parameters (i.e., path loss exponent), and try to estimate the others. In this paper, we adopt graph simultaneous localization and mapping (SLAM) as a general framework for jointly estimating the source positions and parameters of the DRSS sensor array. Our contributions are twofold. On the one hand, by using a Fisher information matrix approach, we conduct a systematic observability analysis of the corresponding SLAM setup for the calibration problem. On the other hand, we propose an effective procedure to select the initial value which is fed to Levenberg-Marquardt iterations for further improving optimization accuracy and convergence. Extensive simulation and hardware experiments show that the proposed method renders high-quality calibration results. All the codes and data are publicly available at https://***/SUSTech2022/DRSS-sensor-array-calibration. © 2023 IEEE.

关键词： Calibration

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Robust Consensus of Perturbed Euler-Lagrange Agents with Unknown Disturbances

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IFAC-PapersOnLine 2024年第6期58卷 190-195页

作者： Alexey Bobtsov Romeo Ortega Jose Guadalupe Romero Emmanuel Nuño Department of Control Systems and Robotics ITMO University Kronverkskiy av. 49 197101 Saint Petersburg Russia Departament of Electrical and Electronic Engineering ITAM Progreso Tizapán 1 04100 Ciudad de México México Department of Computer Science CUCEI University of Guadalajara 44430 Guadalajara Mexico

In this paper we consider the problems of leaderless consensus for networks of fully actuated Euler-Lagrange agents perturbed by unknown additive disturbances. The network is an undirected weighted graph with time delays. The proposed controller has a PD structure that incorporates, in a certainty-equivalent way, the estimate of the unknown disturbance. The design of the disturbance estimator proceeds along the following steps. First, the derivation of a regression equation, that turns out to be nonlinearly parameterized, but with an injective mapping. Second, we propose to use a recently introduced least-squares plus dynamic regressor extension algorithm that allows us to estimate the unknown frequencies imposing extremely weak excitation assumptions. In this way, we derive a sufficient condition on the proportional and derivative gains of the controller to ensure that the systems globally and asymptotically converge to a consensus position.

关键词： Robust adaptive control Multi-agent systems Disturbance rejection Robust time delay systems

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Self-Tuning Robust Tracking control for Autonomous Underwater Vehicles

Self-Tuning Robust Tracking Control for Autonomous Underwate...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Nima Maghooli Fahimeh S. Tabatabaee-Nasab S. Ali A. Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics … Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

This paper addresses the control design problem for a nonlinear and nonholonomic dynamics model of an autonomous underwater vehicle. The kinematics control algorithm is a PID controller while a self-tuning control method is used for trajectory tracking. The kinetics control algorithm is based on an integral sliding mode technique that is robust against time-varying disturbances. The obtained results presented here use the Remote Environmental Monitoring UnitS (REMUS) underwater vehicle model and show the high performance of the controller. Based on the results demonstrated for the two designated trajectories, the tracking quality of self-tuning robust control, despite the significant similarity of the control input of both algorithms for x, y, and z, is much better than the sliding mode control. As a result, AUV was able to follow the desired trajectory, and tracking errors converged to zero. It is worth noting that at non-derivative points of the path (1 st trajectory), tracking errors were entirely within response quality limits (y = ±0.05[m]). The order of control efforts of the proposed control is suitable and can be implemented in the physical system.

关键词： Robust control Autonomous underwater vehicles Mechatronics Trajectory tracking Heuristic algorithms Robot kinematics Trajectory

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HCRI: A ROS2 Human Collision Object Interface for Robotic Manipulation Planning

HCRI: A ROS2 Human Collision Object Interface for Robotic Ma...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Changcong Wang Chongyi Wei Shaoping Bai Yibin Li Xincheng Tian Lelai Zhou the Center for Robotics School of Control Science and Engineering Shandong University Jinan China the Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Department of Materials and Production Aalborg University Aalborg Denmark

Human-Robot Collaboration (HRC) is people and robots work together in the same workspace to achieve shared goals. To ensure safety, robots need to perceive the position of the human body for planning purposes. However, there is no universal method for converting the human body into collision objects. To solve this problem, we propose an interface to convert the human body segments into collision objects in the robot planning scene. The interface estimates the human body Skinned Multi-Person Linear model (SMPL) by RGB image and measures the collision object size of the corresponding body segment. The corresponding size of collision objects are added to the corresponding positions of the human pose estimated by different types of sensors. The accuracy of human size estimation is verified on TotalMocap of AMASS. The interface with OctoMap is compared to evaluate the efficiency and the validity on interface is verified on the robot UR5e.

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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IEEE International Conference on robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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Comparative Study on Fall Detection using Machine Learning Approaches 19

Comparative Study on Fall Detection using Machine Learning A...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Tongskulroongruang, Thienrawit Wiphunawat, Paphatchaya Jutharee, Wisanu Kaewmahanin, Watchara Rassameecharoenchai, Teerameth Jennawasin, Tanagorn Kaewkamnerdpong, Boonserm King Mongkut's University of Technology Thonburi Department of Control Systems and Instrumentation Engineering Bangkok Thailand Institute of Field Robotics and Automation King Mongkut's University of Technology Thonburi Bangkok Thailand Naresuan University Faculty of Allied Health Sciences Department of Cardiothoracic Technology Phitsanulok Thailand King Mongkut's University of Technology Thonburi Biological Engineering Program Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

Falls are one of the most dangerous problems for the elderly. A reliable fall detection system can aid in reducing the harmful repercussions of an unintentional fall. The focus of this paper is on a dataset that includes signals from portable devices. We propose a simple feature selection approach to reduce the number of effective input attributes based on a voting strategy. The dataset is classified into three categories, i.e., pre-fall, fall and post-fall using various machine learning approaches. The computational time is significantly reduced for most of the classification algorithms, and the relative reduction reaches to 66.67% with decision tree algorithm. Classification accuracy can reach as high as 95.17% when using neural network, while the relative reductions on the classification accuracy due to the feature selection do not exceed 1.50%. © 2022 IEEE.

关键词： Decision trees

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