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Homotopic Path Set Planning for Robot Manipulation and Navigation

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arXiv 2024年

作者： Huang, Jing Tang, Yunxi Au, Kwok Wai Samuel Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Multi-Scale Medical Robotics Center Hong Kong

This paper addresses path set planning that yields important applications in robot manipulation and navigation such as path generation for deformable object keypoints and swarms. A path set refers to the collection of finite agent paths to represent the overall spatial path of a group of keypoints or a swarm, whose collective properties meet spatial and topological constraints. As opposed to planning a single path, simultaneously planning multiple paths with constraints poses nontrivial challenges in complex environments. This paper presents a systematic planning pipeline for homotopic path sets, a widely applicable path set class in robotics. An extended visibility check condition is first proposed to attain a sparse passage distribution amidst dense obstacles. Passage-aware optimal path planning compatible with sampling-based planners is then designed for single path planning with adjustable costs. Large accessible free space for path set accommodation can be achieved by the planned path while having a sufficiently short path length. After specifying the homotopic properties of path sets, path set generation based on deformable path transfer is proposed in an efficient centralized manner. The effectiveness of these methods is validated by extensive simulated and experimental results. Copyright © 2024, The Authors. All rights reserved.

关键词： Robot programming

Efficient Reinforcement Learning of Task Planners for Robotic Palletization through Iterative Action Masking Learning

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arXiv 2024年

作者： Wu, Zheng Li, Yichuan Zhan, Wei Liu, Changliu Liu, Yun-Hui Tomizuka, Masayoshi The Department of Mechanical Engineering University of California BerkeleyCA United States The T Stone Robotics Institute The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong The Robotics Institute Carnegie Mellon University PA United States

— The development of robotic systems for palletization in logistics scenarios is of paramount importance, addressing critical efficiency and precision demands in supply chain management. This paper investigates the application of Reinforcement Learning (RL) in enhancing task planning for such robotic systems. Confronted with the substantial challenge of a vast action space, which is a significant impediment to efficiently apply out-of-the-shelf RL methods, our study introduces a novel method of utilizing supervised learning to iteratively prune and manage the action space effectively. By reducing the complexity of the action space, our approach not only accelerates the learning phase but also ensures the effectiveness and reliability of the task planning in robotic palletization. The experiemental results underscore the efficacy of this method, highlighting its potential in improving the performance of RL applications in complex and high-dimensional environments like logistics palletization. © 2024, CC BY.

关键词： Reinforcement learning

GIS-Based Analysis of Water Integrity Differences Within the Madurai Region 2nd

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GIS-Based Analysis of Water Integrity Differences Within the...

2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Balakrishnan, Baranitharan Chandran, Karthik Kannabiran, K. Chowdhury, Subrata Choudhury, Tanupriya Kotecha, Ketan Department of Agricultural Engineering Kalasalingam Academy of Research and Education TN Krishnankoil626126 India Department of Robotics and Automation Jyothi Engineering College KL Chelakkara679531 India Department of Horticulture Kalasalingam Academy of Research and Education TN Krishnankoil626126 India Chittoor AP Murukambattu India CSE Department Graphic Era Deemed to be University Uttarakhand Dehradun248002 India Maharashtra Pune412115 India Pune412115 India

ISBN: (纸本)9789819735938

This present study is mainly concerned with the variations of physicochemical parameters of groundwater samples from different areas of the Madurai region due to different land use and monsoon seasons. Groundwater samples were collected from 40 sample points in and around Madurai city. 14 parameters were considered for the study and physicochemical analysis was done for collected samples. Sampling was done for the monsoon season. Thematic mambos. The study was prepared by visual interpretation of IKONOS satellite imagery using ArcGIS to interpret the water quality index in graphical form. The relationship between Variation in parameters and land use change is interpreted using Statistical Package for the Social Science (SPSS) software. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Land use

Online Robot Motion Planning Methodology Guided by Group Social Proxemics Feature

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arXiv 2025年

作者： Mu, Xuan Liu, Xiaorui Guo, Shuai Chi, Wenzheng Wang, Wei Ge, Shuzhi Sam School of Automation Qingdao University Qingdao266000 China School of Automation Qingdao University Qingdao University Qingdao266000 China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Suzhou215021 China School of Mechanical Engineering & Automation the Robotics Institute Beihang University Beijing100000 China Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore

Nowadays robot is supposed to demonstrate human-like perception, reasoning and behavior pattern in social or service application. However, most of the existing motion planning methods are incompatible with above requirement. A potential reason is that the existing navigation algorithms usually intend to treat people as another kind of obstacle, and hardly take the social principle or awareness into consideration. In this paper, we attempt to model the proxemics of group and blend it into the scenario perception and navigation of robot. For this purpose, a group clustering method considering both social relevance and spatial confidence is introduced. It can enable robot to identify individuals and divide them into groups. Next, we propose defining the individual proxemics within magnetic dipole model, and further established the group proxemics and scenario map through vector-field superposition. On the basis of the group clustering and proxemics modeling, we present the method to obtain the optimal observation positions (OOPs) of group. Once the OOPs grid and scenario map are established, a heuristic path is employed to generate path that guide robot cruising among the groups for interactive purpose. A series of experiments are conducted to validate the proposed methodology on the practical robot, the results have demonstrated that our methodology has achieved promising performance on group recognition accuracy and path-generation efficiency. This concludes that the group awareness evolved as an important module to make robot socially behave in the practical scenario. © 2025, CC BY-NC-ND.

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A Novel Method Based on UNET for Bearing Fault Diagnosis

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Computers, Materials & Continua 2021年第10期69卷 393-408页

作者： Dileep Kumar Soother Imtiaz Hussain Kalwar Tanweer Hussain Bhawani Shankar Chowdhry Sanaullah Mehran Ujjan Tayab Din Memon National Centre of Robotics and Automation HHCMS LabMehran University of Engineering&TechnologyJamshoro76020SindhPakistan Department of Electrical Engineering DHA SUFFA UniversityKarachiSindhPakistan Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76020SindhPakistan

Reliability of rotating machines is highly dependent on the smooth rolling of ***,it is very essential for reliable operation of rotating machines to monitor the working condition of bearings using suitable fault diagnosis and condition monitoring *** the recent past,Deep Learning(DL)has become applicable in condition monitoring of rotating machines owing to its *** paper proposes a novel bearing fault diagnosis method based on the processing and analysis of the vibration *** proposed method is the UNET model that is a recent development in DL *** model is applied to the 2D vibration images obtained by transforming normalized amplitudes of the time-series vibration data samples into the corresponding vibration *** UNET model performs pixel-level feature learning using the vibration images owing to its unique *** results demonstrate that the model can perform dense predictions without any loss of label information,generally caused by the sliding window labelling *** comparative analysis with other DL models confirmed the superiority of the UNET model which has achieved maximum accuracy of 98.91%and F1-Score of 99%.

关键词： Condition monitoring deep learning fault diagnosis rotating machines vibration

Nussbaum Function Based PID Approach for Tracking Control of Robot Manipulators

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Nussbaum Function Based PID Approach for Tracking Control of...

Mediterranean Conference on Control and automation (MED)

作者： Hamed Rahimi Nohooji Holger Voos Interdisciplinary Centre for Security Reliability and Trust (SnT) Automation Robotics Research Group University of Luxembourg Department of Engineering Interdisciplinary Centre for Security Reliability and Trust (SnT) Automation Robotics Research Group Faculty of Science Technology and Medicine (FSTM) University of Luxembourg

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

This paper introduces a novel Nussbaum function-based PID control for robotic manipulators. The integration of the Nussbaum function into the PID frame-work provides a solution with a simple structure that effectively tackles the challenge of unknown control di-rections. Stability is achieved through a combination of neural network-based estimation and Lyapunov analysis, facilitating automatic gain adjustment without the need for system dynamics. Our approach offers a gain determination with minimum parameter requirements, significantly reducing the complexity and enhancing the efficiency of robotic manipulator control. The paper guarantees that all signals within the closed-loop system remain bounded. Lastly, numerical simulations validate the theoretical framework, confirming the effectiveness of the proposed control strategy in enhancing robotic manipulator control.

关键词： Technological innovation PI control Estimation Stability analysis Trajectory Complexity theory PD control

Machine Learning in Predicting the Impact of Filter Parameters on the Accuracy of Biosignal Measurement

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Machine Learning in Predicting the Impact of Filter Paramete...

Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Yeldos A. Altay Raisa K. Uskenbayeva Abu-Alim E. Ayazbay Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Institute of Automation and Information Technologies Vice-Rector Satbayev University Almaty Kazakhstan Electronic engineering Almaty University of Power Engineering and Telecomunications Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

In this scientific article under consideration, a machine learning model has been developed that allows predicting the impact of filter parameters on the accuracy of measuring a biosignal - an ECG (electrocardiography) signal. For the first time, quantitative results have shown the degree of influence and the error introduced into the measured biosignal and described through dependence. The results of assessing the obtained relationship of indicators demonstrate an inverse correlation relationship that characterizes a decrease in the accuracy of measurement at the output of a high-order digital filtering system. The machine learning model is based on the linear regression method the dependence of which is approximated by the method based on least squares and visualized using a scattergram. The adequacy of the developed machine learning model was confirmed by calculating the coefficient of determination and checking its statistical significance. The developed model can be used to create new or improve existing biomedical data processing systems to increase the reliability of the results.

关键词： Accuracy Shape Filtering Biological system modeling Machine learning Biomedical measurement Electrocardiography Distortion Distortion measurement Digital filters

Kinetostatic Model of Redundant Actuation Modes in a Lockable Variable Geometry Truss Manipulator Driven by Flexible Limbs 24th

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Kinetostatic Model of Redundant Actuation Modes in a Lockabl...

24th IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2024

作者： Zhao, Yinjun Xi, Fengfeng Hao, Guangbo Tian, Yingzhong Li, Long Wang, Jieyu School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China Department of Aerospace Engineering Toronto Metropolitan University Toronto ON Canada School of Engineering and Architecture-Electrical and Electronic Engineering University College Cork Cork Ireland

ISBN: (纸本)9789819614639

Manipulators consisting of multiple large deformation limbs can flexibly change their shapes and separate actuation systems from mechanism body, making them particularly suitable for requirements of compact design space, and continuous and versatile deformation. However, the low structural stiffness restricts their practical applications. To enhance the stiffness, we have integrated lockable variable geometry truss (LVGT) supports within the manipulator design. Depending on the number of locked branches within the LVGT, the active flexible limbs may exhibit redundant actuation modes, meaning that the number of working actuators exceeds the DOF of the internal LVGT. The redundant actuation modes, while beneficial for enabling heavier load manipulation, poses challenges in mechanical analysis, necessitating a comprehensive consideration of factors such as motion constraints from rigid joints, nonlinear coupling deformations in the flexible limbs, and control strategies for the redundant actuators. In this paper, we construct a mechanical analysis framework tailored for such operating modes. This framework enables the kinetostatic analyses under the consideration of distributing redundant actuation forces. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Flexible limb actuation Kinetostatic model Redundant actuation

Global Stabilization of Antipodal Points on n-Sphere with Application to Attitude Tracking

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arXiv 2023年

作者： Tong, Xin Cheng, Shing Shin Department of Mechanical and Automation Engineering CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Department of Mechanical and Automation Engineering CUHK T Stone Robotics Institute Shun Hing Institute of Advanced Engineering Multi-Scale Medical Robotics Center The Chinese University of Hong Kong Hong Kong

Existing approaches to robust global asymptotic stabilization of a pair of antipodal points on unit n-sphere Sn typically involve the non-centrally synergistic hybrid controllers for attitude tracking on unit quaternion space. However, when switching faults occur due to parameter errors, the non-centrally synergistic property can lead to the unwinding problem or in some cases, destabilize the desired set. In this work, a hybrid controller is first proposed based on a novel centrally synergistic family of potential functions on Sn, which is generated from a basic potential function through angular warping. The synergistic parameter can be explicitly expressed if the warping angle has a positive lower bound at the undesired critical points of the family. Next, the proposed approach induces a new quaternion-based controller for global attitude tracking. It has three advantageous features over existing synergistic designs: 1) it is consistent, i.e., free from the ambiguity of unit quaternion representation;2) it is switching-fault-tolerant, i.e., the desired closed-loop equilibria remain asymptotically stable even when the switching mechanism does not work;3) it relaxes the assumption on the parameter of the basic potential function in literature. Comprehensive simulation confirms the high robustness of the proposed centrally synergistic approach compared with existing non-centrally synergistic approaches. © 2023, CC BY-NC-ND.

关键词： Hybrid systems