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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Wang, Ruochao Quan, Xiaolong Xiao, Hang Du, Rongjie Qin, Boyang Shi, Qing Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China

ISBN: (纸本)9798350372601

Constrained by the performance of actuators and controllers, achieving stable walking in small-scale quadruped robots has been more challenging compared to larger ones. Rats, in their natural habitat, can achieve stable walking even in extreme environments like narrow spaces by utilizing crawling motion to lower their center of mass. Inspired by this, we conducted a comparative study of the walking stability between crawling and trot gaits on a ratinspired robot named SQuRo. Initially, we collected motion data for both crawling and trot gaits of SQuRo in a simulated environment. Subsequently, we analyzed the dynamic stability of the robot using Poincaré maps. The results indicate that SQuRo's phase trajectories converged into closed loops with periodicity under both gaits, demonstrating the presence of limit cycles. Moreover, fixed points were observed in the Poincaré maps for both gaits, suggesting the dynamic stability of quadrupedal locomotion. Compared to the trot gait, the convergence loops of the crawling gait phase trajectories were smaller, indicating more stable locomotion. We tested the performance of SQuRo's crawling gait in challenging outdoor environments, where SQuRo demonstrated stable walking consistently. This work provides a new approach for achieving stable walking in small-scale quadruped robots and can be readily applied to controller design across different sizes of legged robots. © 2024 IEEE.

关键词： Rats

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Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat

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Cyborg and Bionic systems 2023年第1期4卷 225-232页

作者： Hongzhao Xie Zihang Gao Guanglu Jia Shingo Shimoda Qing Shi Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China Nagoya University Graduate School of Medicine NagoyaJapan

In this paper,we propose a novel method for emulating rat-like behavioral interactions in robots using reinforcement ***,we develop a state decision method to optimize the interaction process among 6 known behavior types that have been identified in previous research on rat *** novelty of our method lies in using the temporal difference(TD)algorithm to optimize the state decision process,which enables the robots to make informed decisions about their behavior *** assess the similarity between robot and rat behavior,we use Pearson *** then use TD-λto update the state value function and make state decisions based on *** robots execute these decisions using our dynamics-based *** results demonstrate that our method can generate rat-like behaviors on both short-and long-term timescales,with interaction information entropy comparable to that between real ***,our approach shows promise for controlling robots in robot-rat interactions and highlights the potential of using reinforcement learning to develop more sophisticated robotic systems.

关键词： robot enable similarity

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Explosive Electric Actuator and Control for Legged robots

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Engineering 2022年第5期8卷 39-47页

作者： Fei Meng Qiang Huang Zhangguo Yu Xuechao Chen Xuxiao Fan Wu Zhang Aiguo Ming School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Biomimetic Robots and Systems Ministry of EducationBeijing 100081China Department of Mechanical and Intelligent Systems Engineering The University of Electro-CommunicationsTokyo 182-8585Japan

Unmanned systems such as legged robots require fast-motion responses for operation in complex *** systems therefore require explosive actuators that can provide high peak speed or high peak torque at specific moments during dynamic *** hydraulic actuators can provide a large force,they are relatively inefficient,large,and *** electric actuators are incapable of providing instant high *** addition,the constant reduction ratio of the reducer makes it difficult to eliminate the tradeoff between high speed and high torque in a given *** study proposes an explosive electric actuator and an associated control method for legged ***,a high-power-density variable transmission is designed to enable continuous adjustment of the output speed to torque ratio.A heat-dissipating structure based on a composite phase-change material(PCM)is *** integral torque control method is used to achieve periodic and controllable explosive power *** experiments are conducted with typical legged robots to verify the effectiveness of the proposed actuator and control ***-legged,quadruped,and humanoid robots jumped to heights of 1.5,0.8,and 0.5 m,*** are the highest values reported to date for legged robots powered by electric actuators.

关键词： Electric actuator Variable transmission Integral torque control Legged robot

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Multi-camera wide field-of-view compound eye imaging system 11

Multi-camera wide field-of-view compound eye imaging system

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Optoelectronic Imaging and Multimedia Technology XI 2024

作者： Qiao, Zhibo Hao, Qun Liu, Mengyao Wei, Jiale Cheng, Yang Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy Beijing Institute of Technology Jiaxing314019 China National Key Laboratory on Near-Surface Detection Beijing100072 China

ISBN: (纸本)9781510682061

With the rapid development of security surveillance and autonomous driving, the demand for wide field-of-view imaging is increasingly growing. Traditional wide field-of-view (FOV) single-camera systems often suffer from significant distortion, making it challenging to achieve comprehensive environmental perception. Compound eyes, with tightly packed multiple sub-eyes, have the advantages of being compact, lightweight, and possessing a wide FOV with high sensitivity to moving targets. This paper analyzes the characteristics of wide FOV imaging of biomimetic compound eyes and integrates the imaging features of multiple cameras to design a multi-camera imaging system based on a biomimetic compound eye imaging system. The proposed system comprises nine cameras with a resolution of 640×480 arranged in a spherical multi-row configuration to emulate the compound eye structure. Given that feature matching significantly impacts the effectiveness of video stitching, we analyze and compare existing typical feature-matching algorithms from the aspects of both matching accuracy and robustness. Consequently, we employ the LightGlue on top of SuperPoint features for feature point matching to ensure the accuracy of subsequent video stitching. Through imaging experiments, the results demonstrate that this video stitching algorithm achieves satisfactory stitching results with minimal mismatches. The proposed multi-camera wide field-of-view compound eye imaging can realize wide wide-field imaging of 170°×120°with 8 frames per second. © 2024 SPIE.

关键词： Imaging systems

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Movement Primitives with Explicit Constraints for Imitation Learning of Pick-and-Place Action 5

Movement Primitives with Explicit Constraints for Imitation ...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Dong, Yue Yu, Zhangguo Chen, Xuechao Wang, Chenzheng Huang, Qiang Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing100081 China

ISBN: (纸本)9798350307320

Movement primitives are the basic units of motions for complex behaviors. They are widely used in imitation learning because they provide leaning and generalizing operator for demonstrated behaviors. As a trajectory-level encoding method, movement primitives have encountered problems when learning and generalizing under certain constraints. This paper proposes Movement Primitives with Explicit Constraints (MPs-EC) for the imitation learning of pick-and-place actions. This methodology learns constraints from demonstration and then reproduces them in generalized trajectories. Meanwhile, an optimization method converts the learned constraints into the scalar weight of a target object to realize constraint reproduction. In this way, the stable constraint reproduction in the generalized trajectory ensures successful tasking. A simulation of fixed orientation pick-and-place action and an experiment of dual-arm pick-and-throw action verify the effectiveness of the proposed movement primitives. © 2023 IEEE.

关键词： Trajectories

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Design of an Impact-resistant Elbow Mechanism for Wheel-legged Robot Crawling 5

Design of an Impact-resistant Elbow Mechanism for Wheel-legg...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Ma, Xiaoshuai Gao, Junyao Qiu, Xuejian Zhao, Lingxuan Chen, Xuechao Yu, Zhangguo Huang, Qiang Beijing Institute of Technology School of Mechatronic Engineering Beijing100081 China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing100081 China

ISBN: (纸本)9798350307320

Wheel-legged robots utilize their arms for efficient crawling in low and narrow passages. However, during the transition from standing to crawling motion mode, wheeled-legged robots, which are underactuated systems, are susceptible to falling and potential damage. Additionally, the elbow joint requires a high torque during robot crawling. Therefore, we designed an elbow mechanism driven by a linear actuator for BIT- W robot. The torque requirement of the elbow joint is analyzed by constructing a crawling model of the robot. Subsequently, a novel optimization method is proposed to enhance impact resistance by optimizing the mechanical parameters. Finally, The experiments conducted validate the elbow mechanism's capability to provide stable support for crawling and motion mode switching. Moreover, the impact mitigation factor (IMF) results substantiate the mechanism's effective enhancement of the arm's impact-resistant ability. © 2023 IEEE.

关键词： Linear actuators

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Distributed Solver for Discrete-Time Lyapunov Equations over Dynamic Networks with Linear Convergence Rate

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IEEE Transactions on Cybernetics 2022年第2期52卷 937-946页

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

The problem of solving discrete-Time Lyapunov equations (DTLEs) is investigated over multiagent network systems, where each agent has access to its local information and communicates with its neighbors. To obtain a solution to DTLE, a distributed algorithm with uncoordinated constant step sizes is proposed over time-varying topologies. The convergence properties and the range of constant step sizes of the proposed algorithm are analyzed. Moreover, a linear convergence rate is proved and the convergence performances over dynamic networks are verified by numerical simulations. © 2013 IEEE.

关键词： Convex optimization

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A comparative study of data-driven battery capacity estimation based on partial charging curves

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Journal of Energy Chemistry 2024年第1期88卷 409-420,I0010页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Xianggong Zhang Enhu Li Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina Department of Electrical Engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina Wuhan Institute of Marine Electric Propulsion China State Shipbuilding Corporation LimitedWuhan 430064HubeiChina Gresgying Digital Technology Ltd. Xi’an 710086ShaanxiChina

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

关键词： Lithium-ion battery Partial charging curves Capacity estimation Data-driven Sampling frequency

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Dynamic Obstacle Avoidance for Magnetic Helical Microrobots Based on Deep Reinforcement Learning

Dynamic Obstacle Avoidance for Magnetic Helical Microrobots ...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Qiu, Yukang Hou, Yaozhen Yang, Haotian Gao, Yigao Huang, Hen-Wei Shi, Qing Huang, Qiang Wang, Huaping Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing100081 China Harvard Medical School Laboratory for Translational Engineering CambridgeMA02139 United States Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9798350372601

Magnetic helical microrobots hold immense promise in biomedical domains owing to their compact size and efficient propulsion capabilities. However, navigating these microrobots through dynamic and unstructured environments, particularly when encountering numerous dynamic obstacles, remains a formidable challenge. In the study, a control framework based on deep reinforcement learning (DRL) with the objective of guiding a microrobot through dynamic obstacles towards specified target goals is introduced. Initially, we design and fabricate a microdrill capable of propulsion via external magnetic rotating fields produced by our magnetic actuation system. Subsequently, we construct a custom training environment, adhering to the OpenAI gym interface, to serve as the simulator for training purposes. Utilizing the proximal policy optimization algorithm, we conduct training of the navigation policy within this simulator. Simulations and experimental validations conducted in dynamic environments affirms the efficacy of the proposed method. © 2024 IEEE.

关键词： Microrobots

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Design and Experiment of Multi-Modal Intelligent Elderly Assisted Wheelchair Robot 8

Design and Experiment of Multi-Modal Intelligent Elderly Ass...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Zhang, Yulin Mao, Han Yu, Shuting Zhu, Aibin Wang, Xin Wang, Na Zhang, Zheng Xu, Haibo Institute of Robotics & Intelligent Systems Xi'An Jiaotong University Shaanxi Key Laboratory of Intelligent Robots Xi'an710049 China Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi'an710049 China

ISBN: (纸本)9798350300178

In response to the prevalent social issue of elderly individuals living alone who lack independent mobility and face difficulties in standing up and getting up, a multi-modal intelligent elderly assistance wheelchair robot has been developed to provide assistance in such scenarios. This paper presents the analysis of the assistance needs of the elderly, along with the proposed main functions of the robot. The mechanical structure of the robot was designed and verified through finite element analysis, followed by experimental verification of assisted standing, transformation of bed and chair form, assisted getting up, and knee-free bending assisted getting up functions. The results of the experiments demonstrate that the multi-modal intelligent wheelchair robot developed in this study can effectively assist the elderly living alone in completing the actions of getting up and standing, thereby reducing their physical burden in home activities and improving their quality of life. This development has potential for broader applicability in the field of elderly care. © 2023 IEEE.

关键词： Machine design

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