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Dictionary-Labeled A∗: Optimal Path-and-Posture Planning for Mobile Robots with Turning Radius Constraints

IEEE Robotics and Automation Letters 2024年第12期9卷 10740-10747页

作者： Yang, Chen Lin, Zhiyun Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen518055 China Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Shenzhen518055 China Peng Cheng Laboratory Shenzhen518066 China

In this study, we introduce an algorithm called Dictionary-Labeled A∗ (DL-A∗), which addresses the critical problem of path-and-posture planning for mobile robots with turning radius constraints. DL-A∗ utilizes a dictionary to store and process multi-element information within an enhanced topological map. The algorithm categorizes the edges in the map into forward driving and reverse driving states, and constructs sets of successive states that adhere to road segment constraints through map pre-processing. Subsequently, the A∗ algorithm is employed to find an optimal path to reach the endpoint while satisfying the end posture constraint, with the objective of minimizing the total travelling cost. Simulation results demonstrate that, in comparison to other popular algorithms, our algorithm offers the capability to adapt the robot's forward and reverse driving postures to minimize total cost, and exhibits exceptional searching efficiency. © 2016 IEEE.

关键词： Robot programming

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Multi-Agent Reinforcement Learning with Region Division and Leader-Follower Communication

Multi-Agent Reinforcement Learning with Region Division and ...

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2024 China Automation Congress, CAC 2024

作者： Wang, Chao Xu, Xiang Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9798350368604

The integration of multi-agent reinforcement learning (MARL) into complex systems has paved new ways for collaborative problem-solving. However, traditional approaches to MARL frequently encounter the challenge of achieving efficient communication among agents, essential for coordinated action. This paper introduces a region division and leader-follower(RDLF) communication algrithm with the MARL framework. RDLF divides the environment into several regions, each managed by a leader agent that coordinates the actions of follower agents and handling inter-region communication. This hierarchical structure reduces unnecessary communication, enhancing learning efficiency. Experimental results in multi-particle environments demonstrate RDLF’s superiority over existing MARL algorithms, especially with increasing agent numbers. RDLF effectively addresses scalability and communication challenges in large-scale multi-agent systems, providing a robust foundation for its application in complex and dynamic environment. © 2024 IEEE.

关键词： Adversarial machine learning

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Path Optimization Method for the Spherical Underwater Robot in Unknown Environment

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Journal of Bionic Engineering 2020年第5期17卷 944-958页

作者： Jian Guo Chunying Li Shuxiang Guo Tianjin Key Laboratory for Control Theory&Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of TechnologyTianjin 300384China Department of Intelligent Mechanical Systems Engineering Faculty of EngineeringKagawa UniversityTakamatsu 761-0396Japan

One of the major respects of the autonomous capability of underwater robots in unknown environment is to be capable of global path planning and obstacles avoiding when encountering abrupt *** the Spherical Underwater Robot(SUR)to fulfill autonomous task execution,this paper proposed a novel fuzzy control method that incorporates multi-sensor technology to guide underwater robots in unknown *** attain the objective,a SUR we designed is used to design the *** to its kinematic model,the safety distance was calculated and sensors(US1000-21 A)were *** novel fuzzy control method was then explored for robot's path planning in an unknown environment through *** simulation results demonstrate the capability of the proposed method to guide the robot,and to generate a safe and smooth trajectory in an unknown *** effectiveness of the proposed method was further verified through experiments with a SUR in a real *** real environment experiments by using the novel fuzzy control method were compared with the basic control *** experimental results show that in unknown environments,the proposed method improves the execution efficiency and flexibility of the SUR.

关键词： path planning fuzzy control spherical underwater robot unknown environment

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Multi-Level Robotic Pouring Using Offline Reinforcement Learning

Multi-Level Robotic Pouring Using Offline Reinforcement Lear...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Zhang, Xiaoxiong Liu, Junwei Zhang, Wei School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Shenzhen518055 China

ISBN: (纸本)9781665481090

This paper presents a novel learning-based method for a robotic manipulator to achieve liquid pouring across different liquid levels using only visual sensors. Previous works have relied on either online reinforcement learning or imitation learning, which are limited by sim-to-real gaps or data efficiency. In this paper, we propose to combine supervised learning and offline reinforcement learning, utilizing a human demonstration dataset containing only successful pouring at the highest level. Specifically, our approach employs supervised learning for a visual classifier, transforming the visual input into a categorical distribution over liquid levels. The offline reinforcement learning method is applied to a binary-conditioned control policy, which takes a binary signal and the robot's proprioception as inputs to determine the action. The binary signal indicates whether the desired liquid level has been reached based on the target liquid level. Through experiments, our method demonstrates superior effectiveness compared to a state-of-the-art imitation learning algorithm. Moreover, tests in unseen scenarios and multiple liquid level commands verify the generalization and transferability of our approach. © 2024 IEEE.

关键词： Self-supervised learning

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Study on Decentralization of Spherical Amphibious Multi-robot control System Based on Smart Contract and Blockchain

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Journal of Bionic Engineering 2021年第6期18卷 1317-1330页

作者： Shuxiang Guo Sheng Cao Jian Guo Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of TechnologyBinshui Xidao Extension 391Tianjin300384China Intelligent Mechanical Systems Engineering Department Faculty of Engineering Kagawa UniversityTakamatsuKagawaJapan

With the development of intelligent bionic robots and the improvement of military application,a single robot cannot meet the requirements of the tasks of the current *** more complex tasks require not only that the robot be able to pass through the field barriers and the amphibious environment,but also that the robot be able to collaborate in a multi-robot ***,research on the multi-robot control system of spherical amphibious robots is very ***,the main research on amphibious robots is to improve the functions of a single robot,in the absence of the study of the multi-robot control *** systems primarily use a centralized control *** the transfer of central node can be achieved,there is still a problem of Byzantine fault tolerance in military applications,that is,when the amphibious multi-robot system is invaded by the *** central node may not only fail to accomplish the task,but also lose control of other robots,with severe *** solve the above problems,this paper proposed a decentralized method of spherical amphibious multi-robot control system based on blockchain ***,the point-to-point information network based on long range radio technology of low power wide area network was set up,we designed the blockchain system for embedded application environment and the decentralized hardware and software architecture of multi-robot control *** this basis,the consensus plugin,smart contract and decentralized multi-robot control algorithm were designed to achieve *** experimental results of consensus of spherical amphibious multi-robot showed the effectiveness of the decentralization.

关键词： Amphibious robot Blockchain Smart contract control system Decentralization

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Attitude Tracking control for Rigid Spacecraft with Arbitrary Convergence Time

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Journal of systems Science & Complexity 2024年第6期37卷 2579-2594页

作者： XU Yu-Tian WU Ai-Guo Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Key University Laboratory of Mechanism&Machine Theory and Intelligent Unmanned Systems of Guangdong Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Department of Automation Harbin Institute of Technology(Shenzhen)Shenzhen 518055China HIT Wuhu Robot Technology Research Institute Wuhu 241060China

In this paper,attitude tracking control with arbitrary convergence time for rigid spacecraft is ***,a novel time-varying sliding function is proposed to achieve free-will arbitrary time convergence when the system states reside on the sliding *** such a sliding function,an attitude tracking controller is designed to guarantee that the states of the closed-loop system converge to the sliding surface within a predetermined time in the presence of external *** free-will arbitrary time convergences of the closed-loop system and sliding function are illustrated by numerical simulations.

关键词： Attitude tracking free-will arbitrary time stability rigid spacecraft sliding mode control

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On the leader-following exponential consensus of discrete-time linear multi-agent systems over jointly connected switching networks

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control theory and Technology 2023年第3期21卷 469-477页

作者： Tao Liu Jie Huang Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055GuangdongChina Shenzhen Research Institute The Chinese University of Hong KongShenzhen 518057GuangdongChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina

The leader-following asymptotic consensus problem for general discrete-time linear multi-agent systems over jointly con-nected switching networks was solved about a decade ***,the leader-following exponential consensus was further established using the so-called Krasovskii-LaSalle theorem for a class of discrete-time linear switched *** this method involves some advanced concepts such as the weak zero-state detectability of some limiting *** this paper,we offer a simpler solution to the leader-following exponential consensus problem for general discrete-time linear multi-agent systems over jointly connected switching *** converting the solvability of the problem to the establishment of the exponential stability for a class of discrete-time linear switched systems,we first show that this class of linear switched systems is uniformly completely ***,we further conclude that the uniform complete observability for this class of linear switched systems implies the exponential stability for the same class of linear switched systems,thus leading to the solution of the leader-following exponential consensus ***,our approach also gives rise to an explicit characterization of the exponential convergence rate of the leader-following consensus problem.

关键词： Leader-following consensus Exponential stabilization-Linear switched systems Discrete-time systems

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Robust Bounded-H8 control for High-Order Fully Actuated systems Based on FAS Approaches 3

Robust Bounded-H8 Control for High-Order Fully Actuated Syst...

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3rd Conference on Fully Actuated System theory and Applications, FASTA 2024

作者： Hu, Liyao Duan, Guangren Harbin Institute of Technology Center for Control Theory and Guidance Technology Harbin150001 China Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Shenzhen518055 China

ISBN: (纸本)9798350373691

This paper investigates the robust bounded-H8 stabilization for a class of high-order fully actuated systems (FASs) with time-varying uncertainty and disturbance. Based on the FAS approaches and the H8 control, a robust bounded-H8 controller is designed, which guarantees that the system state and its derivatives of each order are globally bounded. Furthermore, a combined disturbance, composed of part time-varying uncertainty and disturbance, is given. With the help of the combined disturbance, the impact of the uncertainty and the disturbance on system output can be attenuated simultaneously, because the closed-loop high-order FAS has the bounded-H8 performance. A simulation example is provided to demonstrate the effectiveness of the proposed control method. © 2024 IEEE.

关键词： Robust control

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Decoding split-frequency representation for cross-scale tracking

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Neural Networks 2025年 189卷 107587页

作者： Yuanming Zhang Hao Sun State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin 150001 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin 150001 China Bio-Computing Research Center Harbin Institute of Technology Shenzhen Shenzhen 518055 China

Learning tailored target representations for tracking is a promising direction in visual object tracking. Most state-of-the-art methods utilize autoencoders to generate representations by reconstructing the target’s appearance. However, these reconstructions are often augmented to mimic scale jitter and alteration, neglecting physical scale observations such as those in aerial videos. This article addresses the challenge of representation learning for cross-scale tracking in generalized scenarios. Specifically, we incorporate target scale directly into the positional encoding, indicating scale through relative pixel density rather than the conventional metric of image resolution. This scale-aware encoding is then integrated into the proposed asymptotic hierarchy of decoders, designed to reconstruct representations by emphasizing the restoration of high- and low-frequency features at large and tiny scales. The reconstruction process is guided by supervised learning using split losses, enabling the generation of robust cross-scale representations for generic objects. Extensive experiments on six benchmarks — GOT-10k, LaSOT, TrackingNet, DTB70, UAV123, and TNL2K — validate the superior performance of our method. Additionally, our tracker achieves a remarkable speed of 123 frames per second on a Graphics Processing Unit, surpassing the previous best autoencoder-based tracker. The code and raw results will be made publicly available at: https://***/pellab/DSC .

关键词： Autoencoder Cross-correlation Representation learning Siamese network Visual object tracking

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Implementation and Application of Solvers for Simulation and Execution of control Algorithms in NCSLab 6

Implementation and Application of Solvers for Simulation and...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Su, Jiuzheng Lei, Zhongcheng Hu, Wenshan Liu, Guo-Ping Wuhan University Department of Artificial Intelligence and Automation Wuhan China Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Shenzhen China

ISBN: (纸本)9798350353594

In order to solve the problems of high dependency and low flexibility caused by calling three-party services during simulation and experiments, this paper uses the NCSLab (Networked control System laboratory) as an application platform to implement the functions of multiple ordinary differential equation solvers, which are used for real-time simulation and experimentation of control algorithm. This paper mainly integrates the common ordinary differential equation solving methods and NCSLab platform, and verifies the support of NCSLab platform for different solving methods through the actual simulation process. © 2024 IEEE.

关键词： Networked control systems

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