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arXiv 2024年

作者： Liu, Jinhao Yang, Jun Mao, Jianliang Zhu, Tianqi Xie, Qihang Li, Yimeng Wang, Xiangyu Li, Shihua The School of Automation The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Aeronautical and Automotive Engineering Loughborough University LoughboroughLE11 3TU United Kingdom The College of Automation Engineering Shanghai University of Electric Power Shanghai200090 China

A flexible active safety motion (FASM) control approach is proposed for the avoidance of dynamic obstacles and the reference tracking in robot manipulators. The distinctive feature of the proposed method lies in its utilization of control barrier functions (CBF) to design flexible CBF-guided safety criteria (CBFSC) with dynamically optimized decay rates, thereby offering flexibility and active safety for robot manipulators in dynamic environments. First, discrete-time CBFs are employed to formulate the novel flexible CBFSC with dynamic decay rates for robot manipulators. Following that, the model predictive control (MPC) philosophy is applied, integrating flexible CBFSC as safety constraints into the receding-horizon optimization problem. Significantly, the decay rates of the designed CBFSC are incorporated as decision variables in the optimization problem, facilitating the dynamic enhancement of flexibility during the obstacle avoidance process. In particular, a novel cost function that integrates a penalty term is designed to dynamically adjust the safety margins of the CBFSC. Finally, experiments are conducted in various scenarios using a Universal Robots 5 (UR5) manipulator to validate the effectiveness of the proposed approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Research on target grab of leg-arm cooperative robot based on vision

Research on target grab of leg-arm cooperative robot based o...

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Data Driven control and Learning Systems (DDCLS)

作者： Haichuang Xia Xiaoping Zhang School of Electrical and Control Engineering North China University of Technology Beijing China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Department of Engineering University of Cambridge Cambridge UK

Leg-arm cooperative robot can not only expand the motion space of traditional manipulator, but also make up the operation ability of traditional mobile robot. This paper studies the target grab of leg-arm cooperative robot based on vision. First of all, independently develop the leg-arm cooperative robot. Secondly, for the operation of the manipulator, a height-angle uncoupling PID algorithm is innovatively designed in the cylindrical coordinate system. The target position information obtained by the YOLOv3 algorithm is used as feedback to realize the accurate control of the manipulator, which can avoid the complex process of trajectory planning. Furthermore, combined with three-element trajectory planning method and motion control scheme under triangular gait, a target grab control strategy for the leg-arm cooperative robot is designed, including the height allocation decision maker and the target tracking controller. Finally, the proposed algorithm and schemes are verified with the entity robot.

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Point, Segment, and Inspect: Leveraging Promptable Segmentation Models for Semi-Autonomous Aerial Inspection

Point, Segment, and Inspect: Leveraging Promptable Segmentat...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Riccardo Franceschini Javier Rodriguez Marquez Matteo Fumagalli Julian Cayero Becerra Eurecat Centre Tecnològic de Catalunya Robotics and Automation Unit Cerdanyola del Vallès Barcelona Spain Department of Electrical Engineering Automation and Control Group Danish Technical University Lyngby Denmark

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Operating unmanned aerial vehicles (UAVs) for assets inspections poses distinct challenges encompassing the need to maintain a safe distance from the inspection area, ensure correct orientation towards the inspected surface, and achieve comprehensive coverage of the entire surface. Achieving these tasks is inherently complex and stressful. Therefore, a novel approach that seeks to enhance the piloting experience by harnessing the latest advancements in segmentation models, such as Segment Anything Model (SAM), is proposed. These models, thanks to their prompting capabilities, allow seamless communication between the operator and the UAV, opening up the possibility of defining intricate inspection regions through simple interactions. Within this approach, decision-making authority remains with the operator, while the UAV takes on the demanding task of segmenting the designated area and devising an appropriate traversal plan. Throughout this process, the operator’s situational awareness is heightened through visual cues overlaid on the camera stream and a 3D panel presenting information of the drone position and spatially sensed data. This teleoperation framework allows the operator to maintain continuous control of the ongoing operation through a simplified interface. The paper delineates both the system and the methodology employed, showcasing the effectiveness of integrating segmentation models into the decision-making workflow. The validity of the proposed framework is established through testing within a photorealistic UAV simulator along with real experiments in a controlled laboratory environment.

关键词： Visualization Three-dimensional displays Decision making Laboratories Inspection Traveling salesman problems Autonomous aerial vehicles Robot sensing systems Spatial databases Surface treatment

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A Bi-Level Energy-Efficient Optimization Method for Urban Railway Train Speed Profile and Timetable with an Extended Solution Space

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SSRN 2024年

作者： Pu, Qian Shen, Haikuo Zhu, Liqiang Zhu, Xiaomin Chen, Hongtian The School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China

Energy consumption is one of the key topics of urban railway systems from the perspective of operating costs and environmental friendliness. Interstation speed profile and timetable optimization are two main means to achieve energy saving. A bi-level energy-efficient optimization method is proposed in this study to associate the advantages of speed profile optimization and timetable optimization and reinforce the optimization effect. Firstly, for lower-level optimization, an interstation speed profile optimization model is built based on multiple running schemes, and a multi-objective evolutionary algorithm combined with an analytic function is proposed to obtain Pareto front solutions. Then, for upper-level optimization, an energy-efficient timetable optimization model is constructed based on Pareto front solutions of each running section acquired from lower-level optimization. Accordingly, the solving method with an evolutionary algorithm is proposed to minimize total net energy consumption. Finally, the case study of the Yizhuang line shows the effectiveness of the proposed method and 27.56% overall energy saved. Lastly, the results with different scenes revealed the influence of each level optimization on the overall results. © 2024, The Authors. All rights reserved.

关键词： Operating costs

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Regional Static Output Feedback Stabilization Based on Polynomial Lyapunov Functions for a Class of Nonlinear Systems

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SSRN 2023年

作者： Reis, Gabriela Lígia Araújo, Rodrigo F. Torres, Leonardo A.B. Palhares, Reinaldo M. Federal Institute of Southeast Minas Gerais Department of Education and Technology Brazil Amazonas State University Department of Control and Automation Engineering Brazil Federal University of Minas Gerais Department of Electronics Engineering Brazil

This paper presents a new method for regional stabilization of discrete-time nonlinear systems by Static Output Feedback (SOF) based on polynomial Lyapunov functions. The considered class of nonlinear systems can be described by Difference-Algebraic Representation (DAR) and an equivalent polytopic model is obtained. A convex optimization problem with Linear Matrix Inequality (LMI) constraints is provided to guarantee the system's robust stabilization and to enlarge the estimated Domain of Attraction (DoA). The proposed control design is a one-step approach that can be applied to systems with nonlinear output matrices, and requires no iterative algorithms and/or congruence transformation. Besides that, the use of polynomial Lyapunov functions allows us to obtain asymmetric and non-convex estimated DoA, reducing the conservativeness. Numerical examples are provided to illustrate the advantages of the proposed approach. © 2023, The Authors. All rights reserved.

关键词： Nonlinear systems

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Neural Network Regression Analysis of Magnetic Sensor Data for Spatial Magnet Positioning

Neural Network Regression Analysis of Magnetic Sensor Data f...

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Electrical, Electronic and Computing engineering (IcETRAN), International Conference on

作者： Vladimir Sibinović Mirko Raković Department of Automatic Control Faculty of Electronic Engineering University of Niš Niš Serbia Chair of Mechatronics Robotics and Automation Faculty of Technical Science Novi Sad Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

This paper deals with the magnet position estimation based on the measurements from multiple Hall sensors. Estimation of the position is obtained from trained artificial neural networks. Data are gathered using a custom sensor board that has eight three-axis Hall sensors on it, and correlation between magnetic field and position was determined to be able to estimate position in X and Y directions. First measurements were made to determine the optimal height of the magnet for later data gathering. The outcome of the research was evaluated by comparing the ground truth with the estimated values of the best-trained network to determine the error of estimation. Precise measurement of the position of the magnet is intended to be used for the development of a tactile sensor that estimates the contact force through the displacement of the magnet in the deformable layer.

关键词： Magnetic field measurement Systematics Magnetic sensors Layout Estimation Tactile sensors Artificial neural networks

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Consistency Evaluation of IoT Smart Meter’s Metering Accuracy considering Ambient Temperature and Load Current

Consistency Evaluation of IoT Smart Meter’s Metering Accura...

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System Reliability and Safety engineering (SRSE), International Conference on

作者： Weiming Liu Cen Chen Zhifei Wang Xiaosheng Zhang Guofu Zhai Wei Zheng Department of Electrical Engineering & Automation Harbin Institute of Technology Harbin China Beijing Aerospace Automatic Control Institute Beijing China

The energy meter is a widely used digital-analog electronic system. However, metering accuracy is inevitably influenced by factors such as ambient temperature, load current, and component tolerance. This paper introduces a method utilizing digital twin models to analyze the consistency of metering accuracy in a new single-phase smart meter prototype. An electro-thermal coupling model incorporating a temperature compensation algorithm is established, and the metering accuracy is solved using a surrogate model. By employing the Monte Carlo method, a batch of product samples is generated to determine the impact of varying ambient temperature and load current conditions on the metering accuracy’s consistency within the maximum operating range. The results of this study provides a valuable foundation for robust design and reliability optimization of the energy meter.

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Analyzing Significance of Facial Features for Detection of Parkinson's Disease via Static Images

Analyzing Significance of Facial Features for Detection of P...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Chuang-Chien Chiu Shoou-Jeng Yeh Yen-Chi Sun Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Section of Neurology and Neurophysiology Cheng-Ching General Hospital Taichung Taiwan Master's Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

Parkinson's disease (PD) is a neurodegenerative disorder often characterized by motor symptoms such as hypomimia, and a reduction in facial expression. We explored the significance of facial features in identifying PD through static images, focusing on detecting hypomimia. A dataset comprised of PD patients and healthy controls' static facial images were collected and analyzed. Facial feature detection was conducted using OpenCV and Dlib libraries for the precise localization of key landmarks. In the subsequent feature extraction, parameters such as symmetry, eye aspect ratio, mouth corner distance, muscle tension, and mouth aperture ratio were used. Through the standardization of these features, meaningful comparisons across diverse images were made. By analyzing hypomimia-related features alongside traditional facial parameters, the results provide a comprehensive understanding of the role of facial expressions in PD diagnosis. The findings suggested that examining facial features in static images enhances the accuracy of PD detection and understanding of the nuanced motor symptoms associated with the disease.

关键词： Accuracy Parkinson's disease Sociology Mouth Standardization Muscles Motors

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Collaboration Strategies for Two Heterogeneous Pursuers in A Pursuit-Evasion Game Using Deep Reinforcement Learning

Collaboration Strategies for Two Heterogeneous Pursuers in A...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zhanping Zhong Zhuoning Dong Xiaoming Duan Jianping He The School of Automation Science and Electrical Engineering Beihang University Beijing China The Department of Automation Ministry of Education of China Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We investigate a pursuit-evasion game taking place in an unbounded three-dimensional space, where a flexible pursuer with hybrid dynamics collaborates with a fast pursuer and aims to capture a flexible evader within a finite time. The key feature of this problem lies in the hybrid dynamics of the flexible pursuer, which can change its dynamics once during the game and switch to a fast pursuer with increased speed but lower maneuverability. To address this challenge, we devise a hybrid strategy based on the soft actor-critic framework, tailored specifically for the flexible pursuer, which encompasses both maneuvering and switch tactics. We introduce a switch factor to the input of the actor network and incorporate switch actions to further expand the action space. These additions enable the flexible pursuer to execute maneuvering actions and determine a moment to switch to a fast pursuer. The reward function is designed to account for related angle, altitude, speed, and sparse reward. Through extensive ablation experiments conducted in a simulated environment, we demonstrate the efficacy of our algorithm in facilitating the learning of hybrid strategies for the flexible pursuer, resulting in significantly improved capture rates compared to alternative methods.

关键词： Solid modeling Three-dimensional displays Heuristic algorithms Collaboration Switches Games Deep reinforcement learning Vectors Intelligent robots

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A discrete moth-flame optimization algorithm for multiple automated guided vehicles scheduling problem in a matrix manufacturing workshop

A discrete moth-flame optimization algorithm for multiple au...

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作者： Zeng, Junhai Xie, Wei Pan, Mi School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510641 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangdong Guangzhou510641 China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of Technology Guangdong Guangzhou510641 China Department of Civil and Environmental Engineering University of Macau 999078 China

The growing need for customized and varied production has highlighted the significance of smart and automated factories in the manufacturing sector. In this particular context, the scheduling of multiple Automated Guided Vehicles (AGVs) plays a pivotal role in enhancing the efficiency of operations within an intelligent manufacturing shop. This study centers on the material handling process within a matrix manufacturing shop with the objective of identifying the most cost-effective transportation routes for materials. To accomplish the specified objective, this research aims to identify an optimal solution for reducing transportation costs. In particular, this study formulates a mixed-integer linear programming model and introduces a novel discrete variant of the moth-flame optimization (MFO) algorithm, named DMFO, to address the scheduling problem. The DMFO algorithm incorporates several significant enhancements. Firstly, a population initialization method is proposed, which combines a nearest-neighbor-based adaptive heuristic and a random sorting technique to ensure the formation of a well-structured population. Secondly, the flame generation mechanism and spiral flight search processes within the MFO have been redefined to achieve a more optimal balance between exploration and exploitation. A neighborhood search mechanism is subsequently devised, employing the concept of neighborhood relevance to accelerate the convergence process. Additionally, a heuristic approach is introduced to reduce the computational cost. Moreover, a population regeneration mechanism is proposed to avoid the algorithm falling into a local optimum. To validate the effectiveness of the DMFO, a comparative analysis is conducted using a dataset of 110 real-world factory instances. In this analysis, eight well-established optimization algorithms are employed. The simulation results consistently demonstrate that the relative percentage deviation (RPD) value of the DMFO tends to approach 0% more

关键词： Materials handling

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