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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

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

arXiv

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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

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

arXiv

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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

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Large Language Model-Driven Urban Traffic Signal control

Large Language Model-Driven Urban Traffic Signal Control

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control Conference (ANZCC), Australian and New Zealand

作者： Yiqing Tang Xingyuan Dai Chen Zhao Qi Cheng Yisheng Lv School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Mechanical and Electrical Engineering China University of Mining and Technology at Beijing University of Mining and Technology (Beijing) Inner Mongolia Research Institute Ordos China

In recent years, large language models (LLM) have received a lot of attention for their ability to understand, generate and process natural language. By fine-tuning the models on specific domains or using prompts, LLMs can generate summaries tailored to different contexts and requirements. We hope to utilize these advantages of LLM in urban traffic signal control and provide a new paradigm for traffic control. In this paper, we propose a large language model-driven urban traffic control method, which is designed based on artificial systems, computational experiments, parallel execution (ACP) method. There are three traffic control modes, autonomous mode, feedback mode, and human takeover mode. In autonomous mode, we adopt recommendations based on inventory strategy, which can to some extent reduce the acquisition time of traffic control strategies. With the continuous construction and improvement of the strategic library, the efficiency of the system will be further improved. The feedback mode is mainly aimed at traffic scenarios that are not in the library, generating new control strategies and introducing human feedback. The human takeover model ensures that human engineers have direct control over the actual transportation system. LLM drives the interaction between human engineers and computers in the process of traffic control. Assist human engineers in achieving traffic control and improving work efficiency.

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Inverse Design of a Nurbs-Based Chiral Metamaterial Via Machine Learning for Programmable Mechanical Deformation

SSRN

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SSRN 2024年

作者： Hou, Xiuhui Zhao, Wenhao Zhang, Kai Deng, Zichen School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China School of Aeronautics Northwestern Polytechnical University Xi’an710072 China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Liaoning Dalian116024 China

Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometrical design instead of the chemical composition. To make the mechanical deformation programmable, the Non-Uniform Rational B-Spline (NURBS) curves are taken to replace the traditional ligament boundaries of the chiral structure. The Neural Networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency. For the problem of finding structure configuration with specified mechanical properties, such as Young’s modulus, Poisson’s ratio or deformation, an inverse design method using the Neural Network-based proxy model is proposed to build the relationship between mechanical properties and geometric configuration. To satisfy some more complex deformation requirements, a non-homogeneous inverse design method is proposed and verified through simulation and experiments. Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the design of chiral metamaterials. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

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Learning Pre-Grasp Manipulation of Flat Objects in Cluttered Environments using Sliding Primitives

Learning Pre-Grasp Manipulation of Flat Objects in Cluttered...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jiaxi Wu Haoran Wu Shanlin Zhong Quqin Sun Yinlin Li State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China Department of Automation University of Science and Technology of China Heifei China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing China Science and Technology on Thermal Energy and Power Laboratory Wuhan China

Flat objects with negligible thicknesses like books and disks are challenging to be grasped by the robot because of the width limit of the robot's gripper, especially when they are in cluttered environments. Pre-grasp manipulation is conducive to rearranging objects on the table and moving the flat objects to the table edge, making them graspable. In this paper, we formulate this task as Parameterized Action Markov Decision Process, and a novel method based on deep reinforcement learning is proposed to address this problem by introducing sliding primitives as actions. A weight-sharing policy network is utilized to predict the sliding primitive's parameters for each object, and a Q-network is adopted to select the acted object among all the candidates on the table. Meanwhile, via integrating a curriculum learning scheme, our method can be scaled to cluttered environments with more objects. In both simulation and real-world experiments, our method surpasses the existing methods and achieves pre-grasp manipulation with higher task success rates and fewer action steps. Without fine-tuning, it can be generalized to novel shapes and household objects with more than 85% success rates in the real world. Videos and supplementary materials are available at https://***/view/pre-grasp-sliding.

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Research on the High-Precision Unmanned Operation control Algorithm of theVibroseis Vehicle

Research on the High-Precision Unmanned Operation Control Al...

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第40届中国控制会议

作者： LI Bin WANG Shoukun WANG Shuai WANG Junzheng LIU Shangfei State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing Institute of Technology

In order to meet the demand for high-precision operation of the vibroseis vehicle in the case of unmanned driving, an unmanned operation system that meets the working characteristics of the vibroseis vehicle is designed, and the key technical problems are studied, so that the vibroseis vehicle can operate in the complex environment of the field and improve the efficiency of geological exploration greatly. Firstly, the coordinate system and the kinematic model without sideslip of the articulated vehicle are established successively. Secondly, in order to improve the path tracking accuracy of the vibroseis vehicle, a model predictive control algorithm based on the kinematic model is designed for vehicle path tracking. In order to improve the positioning accuracy of the working point, a compensation algorithm for positioning error is proposed to reduce the positioning error caused by terrain factors. Finally, the unmanned operation platform is built and the path tracking algorithm and the compensation algorithm for positioning error are verified on the platform. The real vehicle test data shows that the path tracking algorithm proposed in this paper can control the average lateral error of the path tracking of the vibroseis vehicle within 22 *** with the PID control method, its path tracking accuracy can be improved by 59%. The average positioning error of working point is controlled within about 15 cm by adopting the compensation algorithm for positioning error.

关键词： Vibroseis vehicle Unmanned operation Path tracking Positioning compensation

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Nonlinear E-field Simulation of HVDC Converter Transformer Busing and Its Structure Optimization With RBF Neural Network and NSGA-II Algorithm

Nonlinear E-field Simulation of HVDC Converter Transformer B...

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IEEE International Conference on Power and Energy systems (ICPES)

作者： Yongsheng He Shiling Zhang Zongxiang Lu Pengbo Wang State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute Chongqing China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Haidian China Dept name of State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing China

Static DC and PR are typical operation conditions of HVDC converter transformer bushing outlet device, moreover, the electrical parameters of RIP, transformer oil and OIP have the nonlinear relationship with E-field stress and temperature. Under the temperature gradient, the electrical parameters will modify the static DC and PR E-field distribution of the composite insulation. In order to simulate static DC and PR electric field of the composite insulation structure, this paper established the full model of the converter transformer outlet. Then, the structure parameters of converter transformer outlet have been optimized using combined RBF neural network and NSGA-II algorithm. Moreover, electric field verification calculation has been carried out under AC and PR conditions. The results show that under uniform temperature condition, E-field strength is larger than that under iso-thermal condition. The overshoot coefficient of the bushing end and barrier reach 65% and 45%, respectively. The study can provide reference for the design of outlet structure of the converter transformer.

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Multiplicative Fault Detection and Isolation in Dynamic systems Using Data-Driven K-Gap Metric based kNN Algorithm

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IFAC-PapersOnLine 2022年第6期55卷 169-174页

作者： Caroline Charlotte Zhu Linlin Li Steven X. Ding Institute of Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Duisburg 47057 Germany Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing 100083 Beijing China

In this paper, a fault detection and isolation scheme for multiplicative faults in dynamic systems based on data-driven K-Gap metric and k-nearest neighbour (kNN) classification is proposed. To detect multiplicative faults, the standard classification task of kNN is studied from the viewpoint of system analysis. To this end, the data-driven stable kernel representation based on input/output data is presented for feature extraction capturing the dynamic of linear time-invariant (LTI) systems. Data-driven K-Gap metric is used as an alternative tool for distance measure between two kernel subspaces in the kNN algorithm. A simulation example on the three-tank system (DTS200) demonstrates the successful detection and isolation of various multiplicative faults

关键词： Fault detection isolation multiplicative faults data-driven methods multiclass classification process monitoring K-Gap gap metrics

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Research on the Impact of Water-Ingression Defects on the Electromagnetic-Thermal Fluctuation and Heat Distribution Characteristics of High Voltage Cable Terminals

SSRN

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SSRN 2023年

作者： Liu, Xingmou Yang, Hui Xu, Qiqi Lin, Haibo Yang, Yongming Jadoon, Ammad Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing University Chongqing400044 China NFC-Institute of Engineering &Technology Multan Pakistan

High voltage cable terminals (HVCT) usually work outdoors with water-ingression defect which affects the normal operation of the power system. This paper presents the study of the influence of different water-ingression depth on the temperature distribution of HVCT. Firstly, the model of EM-thermal-fluid coupling field of HVCT was established using finite element method in line with the structural parameters of YJZWC4 HVCT. Subsequently, the effectiveness of the model is then verified by comparing the operation of the model under the actual HVCT. And then, the analysis results of temperature show that the surface temperature of the HVCT at the inlet part is significantly higher than that of the insulating oil part. And The influent depth is positively correlated with surface temperature and temperature gradient. The distortion of the electric field will be more serious due to the deepening of the depth of the inlet water. Finally, the variation of temperature and field strength with the depth of inlet water is summarized by mathematical fitting method. The research results accurately reflect the electromagnetic thermal characteristics of the HVCT under the influent state and provide a reliable technical means for the state prediction and fault diagnosis of the cable terminals. © 2023, The Authors. All rights reserved.

关键词： Atmospheric temperature

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