检索结果-内蒙古大学图书馆

Moving forward in formation: A decentralized hierarchical learning approach to multi-agent moving together

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Liu, Shanqi Wen, Licheng Cui, Jinhao Yang, Xuemeng Cao, Junjie Liu, Yong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang310027 China

Multi-agent path finding in formation has many potential real-world applications like mobile warehouse robots. However, previous multi-agent path finding (MAPF) methods hardly take formation into consideration. Furthermore, they are usually centralized planners and require the whole state of the environment. Other decentralized partially observable approaches to MAPF are reinforcement learning (RL) methods. However, these RL methods encounter difficulties when learning path finding and formation problem at the same time. In this paper, we propose a novel decentralized partially observable RL algorithm that uses a hierarchical structure to decompose the multi-objective task into unrelated ones. It also calculates a theoretical weight that makes every task’s reward has equal influence on the final RL value function. Additionally, we introduce a communication method that helps agents cooperate with each other. Experiments in simulation show that our method outperforms other end-to-end RL methods and our method can naturally scale to large world sizes where centralized planner struggles. We also deploy and validate our method in a real-world scenario. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

HILONet: Hierarchical imitation learning from non-aligned observations

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Liu, Shanqi Cao, Junjie Chen, Wenzhou Wen, Licheng Liu, Yong The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang310027 China

It is challenging learning from demonstrated observation-only trajectories in a non-time-aligned environment because most imitation learning methods aim to imitate experts by following the demonstration step-by-step. However, aligned demonstrations are seldom obtainable in real-world scenarios. In this work, we propose a new imitation learning approach called Hierarchical Imitation Learning from Observation(HILONet), which adopts a hierarchical structure to choose feasible subgoals from demonstrated observations dynamically. Furthermore, our method can learn different kinds of policy corresponding to different tasks by using a novel reward structure. We also present three different ways to increase sample efficiency in the hierarchical structure. We conduct extensive experiments using several environments. The results show the improvement in both performance and learning efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Efficiency

Adaptive Pseudo Inverse control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic systems

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 916-928页

作者： Xiuyu Zhang Ruijing Jing Zhiwei Li Zhi Li Xinkai Chen Chun-Yi Su School of Automation Engineering Northeast Electric Power Universityand also with Jilin Province International Research Center of Precision Drive and Intelligent ControlJilin 132012China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Electronic and Information Systems Shibaura Institute of TechnologySaitama 337-8570Japan Department of Mechanical and Industrial Engineering Concordia UniversityQCMontreal H3B 1R6Canada

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)***"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is *** main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is *** of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

关键词： Adaptive dynamic surface control adaptive pseudo inverse control asymmetric and saturated hysteresis robust control

Radar-on-Lidar: metric radar localization on prior lidar maps

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Yin, Huan Wang, Yue Tang, Li Xiong, Rong The State Key Laboratory of Industrial Control and Technology The Institute of Cyber-Systems and Control Zhejiang University Hangzhou310058 China

Radar and lidar, provided by two different range sensors, each has pros and cons of various perception tasks on mobile robots or autonomous driving. In this paper, a Monte Carlo system is used to localize the robot with a rotating radar sensor on 2D lidar maps. We first train a conditional generative adversarial network to transfer raw radar data to lidar data, and achieve reliable radar points from generator. Then an efficient radar odometry is included in the Monte Carlo system. Combining the initial guess from odometry, a measurement model is proposed to match the radar data and prior lidar maps for final 2D positioning. We demonstrate the effectiveness of the proposed localization framework on the public multi-session dataset. The experimental results show that our system can achieve high accuracy for long-term localization in outdoor scenes. Copyright © 2020, The Authors. All rights reserved.

关键词： Radar measurement

Mapless-Planner: a robust and fast planning framework for aggressive autonomous flight without map fusion

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Ji, Jialin Wang, Zhepei Wang, Yingjian Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

Maintaining a map online is resource-consuming while a robust navigation system usually needs environment abstraction via a well-fused map. In this paper, we propose a mapless planner which directly conducts such abstraction on the unfused sensor data. A limited-memory data structure with a reliable proximity query algorithm is proposed for maintaining raw historical information. A sampling-based scheme is designed to extract the free-space skeleton. A smart waypoint selection strategy enables to generate high-quality trajectories within the resultant flight corridors. Our planner differs from other mapless ones in that it can abstract and exploit the environment information efficiently. The online replan consistency and success rate are both significantly improved against conventional mapless methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Navigation systems

Consensus-Based Distributed Nonlinear Filtering with Kernel Mean Embedding

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Guo, Liping Wang, Jimin Zhao, Yanlong Zhang, Ji-Feng The Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China The School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China The Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China

This paper proposes a consensus-based distributed nonlinear filter with kernel mean embedding (KME). This fills with gap of posterior density approximation with KME for distributed nonlinear dynamic systems. To approximate the posterior density, the system state is embedded into a higher-dimensional reproducing kernel Hilbert space (RKHS), and then the nonlinear measurement function is linearly converted. As a result, an update rule of KME of posterior distribution is established in the RKHS. To show the proposed distributed filter being capable of achieving the centralized estimation accuracy, a centralized filter, serving as an extension of the standard Kalman filter in the state space to the RKHS, is developed first. Benefited from the KME, the proposed distributed filter converges to the centralized one while maintaining the distributed pattern. Two examples are introduced to demonstrate the effectiveness of the developed filters in target tracking scenarios including nearly constantly moving target and turning target, respectively, with bearing-only, range and bearing measurements. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

TGK-Planner: An efficient topology guided kinodynamic planner for autonomous quadrotors

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Ye, Hongkai Zhou, Xin Xu, Chao Chu, Jian Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

In this paper, we propose a lightweight yet effective quadrotor planning system for aggressive flights with limited onboard computing resources. The proposed system follows the traditional hierarchical planning workflow, with novel designs to improve the robustness and efficiency in both the pathfinding and trajectory optimization sub-modules. Firstly, we propose the topology guided graph, which roughly captures the topological structure of the environment and guides the state sampling of a sampling-based kinodynamic planner. In this way, we significantly improve the efficiency of finding a safe and dynamically feasible trajectory. Then, we refine the smoothness and continuity of the trajectory in an optimization framework, which incorporates the homotopy constraint to guarantee the safety of the trajectory. The optimization program is formulated as a sequence of quadratic programmings (QPs) and can be iteratively solved in a few milliseconds. Finally, the proposed system is integrated into a fully autonomous quadrotor and validated in various simulated and real-world scenarios. Benchmark comparisons show that our method outperforms state-of-the-art methods with regard to efficiency and trajectory quality. Moreover, we will release our code as an open-source package. Copyright © 2020, The Authors. All rights reserved.

关键词： Trajectories

Fast-tracker: a robust aerial system for tracking agile target in cluttered environments

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Han, Zhichao Zhang, Ruibin Pan, Neng Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

This paper proposes a systematic solution that uses an unmanned aerial vehicle (UAV) to aggressively and safely track an agile target. The solution properly handles the challenging situations where the intent of the target and the dense environments are unknown to the UAV. Our work is divided into two parts: target motion prediction and tracking trajectory planning. The target motion prediction method utilizes target observations to reliably predict the future motion of the target considering dynamic constraints. The tracking trajectory planner follows the traditional hierarchical workflow. A target informed kinodynamic searching method is adopted as the front-end, which heuristically searches for a safe tracking trajectory. The back-end optimizer then refines it into a spatial-temporal optimal and collision-free trajectory. The proposed solution is integrated into an onboard quadrotor system. We fully test the system in challenging real-world tracking missions. Moreover, benchmark comparisons validate that the proposed method surpasses the cutting-edge methods on time efficiency and tracking effectiveness. Copyright © 2020, The Authors. All rights reserved.

关键词： Motion estimation

CL-MAPF: Multi-Agent path finding for car-like robots with kinematic and spatiotemporal constraints

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Wen, Licheng Zhang, Zhen Chen, Zhe Zhao, Xiangrui Liu, Yong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang310027 China

Multi-Agent Path Finding has been widely studied in the past few years due to its broad application in the field of robotics and AI. However, previous solvers rely on several simplifying assumptions. They limit their applicability in numerous real-world domains that adopt nonholonomic car-like agents rather than holonomic ones. In this paper, we give a mathematical formalization of Multi-Agent Path Finding for Car-Like robots (CL-MAPF) problem. For the first time, we propose a novel hierarchical search-based solver called Car-like Conflict-Based Search to address this problem. It applies a body conflict tree to address collisions considering shapes of the agents. We introduce a new algorithm called Spatiotemporal Hybrid-state A* as the single-agent path planner to generate path satisfying both kinematic and spatiotemporal constraints. We also present a sequential planning version of our method for the sake of efficiency. We compare our method with two baseline algorithms on a dedicated benchmark containing 3000 instances and validate it in real-world scenarios. The experiment results give clear evidence that our algorithm scales well to a large number of agents and is able to produce solutions that can be directly applied to car-like robots in the real world. The benchmark and source code are released in https://***/APRIL-ZJU/CL-CBS. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems