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Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 146-159页

作者： Yinlong Zhang Wei Liang Mingze Yuan Hongsheng He Jindong Tan Zhibo Pang Key Laboratory of Networked Control Systems Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Computing Wichita State UniversityWichita 67260 USA Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeTN 37996 USA Department of Automation Technology ABB Corporate Research SwedenVasteras 72178Sweden Department of Intelligent Systems Royal Institute of Technology(KTH)Stockholm 11428Sweden

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment ***,traditional calibrations suffer inaccuracy and *** address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying *** our method,the spatial relationship is geometrically correlated between the sensing units and robotic *** decoupled estimations on rotation and translation could reduce the coupled errors during the ***,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and *** calibration has been evaluated on our developed *** the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,*** comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

关键词： Calibration inertial measurement unit(IMU) monocular camera robotic arm spiral moving trajectory

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Adaptive Control of Wiener systems with Polynomial Description

Adaptive Control of Wiener Systems with Polynomial Descripti...

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2023 China Automation Congress, CAC 2023

作者： Li, Jiwei Wu, Chen Shi, Enming Zhi, Wenzhuo Zhang, Bi Zhao, Xingang Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (纸本)9798350303759

For plenty of practical applications, Wiener model structures are believed to play important roles for modeling and controller design tasks. Such models have physical insights and are close to realistic systems. This brief tries to introduces a new control scheme based on Wiener models. A criterion function is firstly presented, which fully considers the output tracking and minimizes the control effort. According to reasonable principles, these weighting terms can be easily designed. Derived from the cost function, an extended system of the original plant is further analyzed, the parameters of which are online updated by robust estimator. Then based on these estimates, the control law is developed. Intriguingly, to enhance the tracking performance, the estimate of unmodeled dynamics is designed as an important feedback information as well. Rigorous theoretical analysis has proven the closed-loop system stability. Finally, representative simulation studies have been conducted to show the merits of the novel controller. © 2023 IEEE.

关键词： Model structures

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Visible RRT*: Asymptotically Optimal Random Search Tree for Visual Servo Tasks with the FOV Constraint

Visible RRT*: Asymptotically Optimal Random Search Tree for ...

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Chinese Control Conference (CCC)

作者： Zhejin Zhu Runhua Wang Xuebo Zhang Institute of Robotics and Automatic Information System Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin P. R. China

This paper presents a novel visibility-based asymptotically optimal random search tree trajectory planning algorithm (Visible RRT*), which is dedicated to addressing the visual servoing tasks under the FOV constraint. Firstly, a search tree reconstruction method under the FOV constraint is proposed to obtain an asymptotically optimal solution. Meanwhile, a novel greedy search strategy is designed to improve the searching efficiency by segmenting the greedy results based on the FOV constraint. Finally, comparative simulations are conducted in two challenging scenarios, and the results show that the planned trajectory is asymptotically optimal, thus confirming the effectiveness of the proposed algorithm.

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Route planning of truck and multi-drone rendezvous with available time window constraints of drones

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Science China(Technological Sciences) 2022年第9期65卷 2190-2204页

作者： LIANG ChengYuan LUO Xin CHEN XueDong HAN Bin School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Guangdong Intelligent Robotics Institute Dongguan 523808China

During the scenarios of cooperative tasks performed by a single truck and multiple drones,the route plan is prone to failure due to the unpredictable scenario *** this situation,it is significant to replan the rendezvous route of the truck and drones as soon as possible,to ensure that all drones in flight can return to the truck before running out of *** paper addresses the problem of rendezvous route planning of truck and *** to the available time window constraints of drones,which limit not only the rendezvous time of the truck and drones but also the available period of each drone,there are obvious local optimum phenomena in the investigated problem,so it is difficult to find a feasible solution.A two-echelon heuristic algorithm is *** the algorithm,the strategy jumping out of the local optimum and the heuristic generating the initial solution are introduced,to improve the probability and speed of obtaining a feasible solution for the rendezvous *** results show that the feasible solution of the truck-drones rendezvous route can be obtained with 88%probability in an average of 77 iterations for the scenario involving up to 25 *** influence of algorithm options on planning results is also analyzed.

关键词： truck and multi-drone rendezvous route planning available time window two-echelon heuristic strategy jumping out of local optimum

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Soft robotics:Morphology and Morphology-inspired Motion Strategy

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1500-1522页

作者： Fan Xu Hesheng Wang Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

robotics has aroused huge attention since the *** of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental ***,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured *** decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing *** presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific *** paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

关键词： Soft continuum manipulator soft gripper soft mobile robot soft robot control method soft robot modeling method soft robotics

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A Hierarchical Framework for Dynamic Global Path Planning 10

A Hierarchical Framework for Dynamic Global Path Planning

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10th International Forum on Electrical Engineering and Automation, IFEEA 2023

作者： Fan, Zhiwei Jia, Kai Zhang, Lei Zou, Fengshan Du, Zhenjun Liu, Mingmin Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Shenyang Siasun Robot & Automation Co. Ltd Shenyang China

ISBN: (纸本)9798350309379

This article presents a hierarchical global path planning algorithm designed for mobile robots. The global path planning problem is divided into three distinct components: waypoint generation, reference path generation, and path optimization. In the waypoint generation phase, we allocate the computation of environmental changes and map updates within each frame point cloud based on dynamically updated visibility graph. We then derive waypoints by identifying visibility edge vertices. Next, a smooth reference path is obtained through B-spline fitting optimization, delineating the convex driving region within the environment for further optimization within homotopy classes. To mitigate collision issues arising from B-spline fitting, we formulate the path optimization problem in the Frenet coordinate system as a quadratic programming task. This approach yields a globally collision-free path with high computational efficiency. Simulation experiments have been conducted to validate the effectiveness of the algorithm proposed in this paper. © 2023 IEEE.

关键词： global path planning mobile robot quadratic program visibility graph

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Feature Evaluation for Underwater Acoustic Object Counting and F0 Estimation 4

Feature Evaluation for Underwater Acoustic Object Counting a...

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4th International Conference on robotics and Computer Vision, ICRCV 2022

作者： Li, Liming Song, Sanming Wang, Li Ye, Lei Jing, Yan Pang, Guofu State Key Laboratory of Robotics Shenyang Institute of Automation Cas Shenyang110169 China Institutes for Robotics and Intelligent Manufacturing Cas Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

When carrying out underwater acoustic target detection mission, we need to count the target number (N), conduct source separation when N is greater than one, and retrieve motion parameters (shaft frequency, or F0 for example) of each target from the separated noises. Though widely adopted in image interpretation, deep learning methods, however, strongly depend on the form or quality of the feed-in data or features, especially for underwater acoustic applications where strong ambient noise and multi-path effects hinders accurate target detection. Therefore, a thorough evaluation of typical features can provide a reference for feature selection in different tasks. In this paper, we choose CRNN, which has been widely validated in time-series analysis, as the common classifier to evaluate different time-frequency features and their enhanced version for object counting and F0 estimation. The performance of feeding STFT, GST, LOFAR, DEMON, or MFCCs as input is analyzed in the two tasks respectively through simulation and lake trial. Experimental results based on lake trial dataset show that both LOFAR and DEMON dominate object counting performance, with an accuracy of 96% and 97%, respectively, while DEMON performs better (94%)in F0 estimation task than LOFAR (83%), partly due to the prominent cavitation in our lake trial dataset. STFT and GST have poor robustness in real environment, while MFCCs fails to cope with both tasks. © 2022 IEEE.

关键词： Deep learning

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Ground Mobile Robot Traversable Area Recognition Based on 3D CNN and Attention Mechanism

Ground Mobile Robot Traversable Area Recognition Based on 3D...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Zhang, Qi Shao, Shiliang Wang, Ting Cao, Zonghan Xu, Fuli Shi, Xianyu School of Software Shenyang University of Technology Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9798350316308

As robot technology advances, ground mobile robots have been widely used in dangerous operation environments such as search, rescue, and bomb disposal. The generation of accurate and reliable traversable area maps is crucial for the autonomous navigation of ground mobile robots, especially in rough, uneven, and complex environments. To acquire a more accurate robot traversable area, this paper presents a traversable area identification method based on 3D convolution and attention mechanism. This method uses the 3D LiDAR point cloud information obtained by laser radar scanning. Firstly, it voxelizes the point cloud to improve the identification efficiency. Then, it optimizes the sparse Bird's Eye View Network to identify the voxelized point cloud. A residual module is introduced between the sub-manifold convolution layer and sparse convolution layer of the 3D sparse convolution to solve the training difficulty caused by network depth. In addition, an attention mechanism module is added to the end of point cloud feature extraction to allow the network to pay more attention to useful information in the features. Experimental results show that our network can achieve superior identification results compared to the Bird's Eye View Network. © 2023 IEEE.

关键词： Convolution

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Passive Suspension Design and Dynamics Analysis of Manned Lunar Rover

Passive Suspension Design and Dynamics Analysis of Manned Lu...

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Mechatronics and robotics Engineering (ICMRE), International Conference on

作者： Junyang Zhang Zhen Liu Zhonghao Qin State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Special Robot Equipment Group Harbin Institute of Technology Zhengzhou Research Institute Harbin China

ISBN: (数字)9798350394276

ISBN: (纸本)9798350394283

The lunar surface environment differs significantly from that of Earth, thus necessitating the specialized design of suspension systems for lunar rovers. Within this study, a double wishbone independent suspension system is specifically designed for a manned lunar rover, with its dynamics attributes investigated through theoretical analyses and simulations. Firstly, the structural parameters of the double wishbone suspension are designed. Secondly, the theoretical dynamics model of the suspension is established, the dynamics equations are deduced, and an exploration into the impact of diverse system parameters on the suspension’s dynamics performance is conducted. Finally, the suspension underwent multi-body dynamics analysis using ADAMS to verify compliance with specified requirements for obstacle-crossing performance.

关键词： Space vehicles Suspensions (mechanical systems) Analytical models Mechatronics Moon Mathematical models Shock absorbers

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Robust Robot Control Policy Learning Based on Gaussian Mixture Variational Autoencoders

Robust Robot Control Policy Learning Based on Gaussian Mixtu...

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2024 China Automation Congress, CAC 2024

作者： Dong, Qingwei Zeng, Peng Zang, Chuanzhi Wan, Guangxi Dong, Xiaoting Cui, Shijie State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Shenyang University of Technology Shenyang110870 China

ISBN: (纸本)9798350368604

Reinforcement learning methods have demonstrated advanced capabilities in training neural network controllers for specific tasks. In the industrial domain, where model discrepancies and state disturbances occur, robot control strategies must exhibit adaptability. Existing studies, such as Generative Motor Reflexes (GMR), employ Variational Autoencoders (VAE) to approximate the latent variable space distribution to a standard normal distribution. However, this method, while straightforward, offers limited capability in representing data. The Gaussian Mixture Variational Autoencoder (GMVAE) algorithm leverages a Gaussian Mixture Model (GMM) as the prior distribution for data generation, enhancing the representation of the original state distribution. To increase the robustness of the trained neural network controllers against unknown states, we utilize GMVAE to represent the original state space, subsequently learning the mapping from latent variables to actions. We further accelerate the policy search process by integrating state representation learning with Guided Policy Search (GPS) methods. Our method was evaluated on robotic reaching tasks. Experimental results validate the robustness of our method against state perturbations. © 2024 IEEE.

关键词： Normal distribution

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