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A novel frequency-dependent hysteresis model based on improved neural Turing machine

Science China(Information Sciences) 2023年第1期66卷 330-331页

作者： Yinan WU Yongchun FANG Zhi FAN Cunhuan LIU Institute of Robotics and Automatic Information System College of Artificial IntelligenceNankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University

Dear editor,The inherent hysteresis of a piezoelectric actuator(PEA) results in intricate nonlinearity between the output displacement and input voltage, which restricts positioning accuracy of the actuator [1, 2]. Hysteresis behavior appears as a coupling of nonlinearity, frequency-dependence and memory characteristic, which makes it difficult to comprehensively characterize hysteresis [3]. To eliminate the effect of hysteresis on the positioning accuracy of PEAs,

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Multi-modal Bionic Motion Analysis of A Cpg-controlled Pneumatic Soft Robot

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Journal of Bionic Engineering 2024年第5期21卷 2247-2257页

作者： Yu Zhang Peiyu Huang Dongjie Li Jiangyu Zhou Yu Li Bo You Yanhe Zhu Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and TechnologyHarbin150080China State Key Laboratory of Robotics and System Harbin Institute of Technology(HIT)Harbin150001China

This paper designs a soft robot with a multi-chamber,multi-airbag mimicking soft biological structure,where the airbags of the same chamber are interconnected with each *** upper and lower chambers are separated by an intermediate layer(thin plate),which is extended and widened to achieve robot movement and *** applying pressure to the different chambers of the soft robot,it is possible to produce a variety of bionic movements of the inchworm and *** to the strong nonlinearity and infinite number of degrees of freedom properties of the material,it is impossible to obtain the analytical solution of the bending morphology and pressure of the soft robot ***,a method to establish a mathematical model of soft robot deformation based on the classical stacked plate theory is proposed,and a chain composite model of soft robot bending motion is established based on the large-deflection modeling *** paper proposes a method to generate a multi-mode soft robot motion control based on the Central Pattern Generator(CPG)using a single controller,which achieves the switching of sine wave-like patterns,half-wave-like patterns,and dragging patterns by adjust-ing frequency,amplitude and period of ***,a pneumatic control platform is built for the validation of the theoretical model and different experimental models of the motion of the *** comparation of the different motion modes of the soft robot under similar non-load and load conditions.

关键词： Soft robot Bionic multi-modal movement Laminated plate theory CPG control

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Contact Force Optimization to Enhance Fault-tolerant Motion Stability of a Hexapod Robot

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Journal of Bionic Engineering 2024年第5期21卷 2199-2214页

作者： Bo You Shangdong Shi Chen Chen Jiayu Li Nan Li Liang Ding The Key Laboratory of Intelligent Technology for Cutting and Manufacturing Ministry of Education and the Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and TechnologyHarbin150080China The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001China

This paper presents a novel method for optimizing the contact force of a hexapod robot to enhance its dynamic motion stability when one of its legs *** proposed approach aims to improve the Force Angle Stability Margin(FASM)and adapt the foot trajectory through contact force optimization to achieve safe and stable motion on various *** foot force optimization approach is designed to optimize the FASM,a factor rarely considered in existing contact force optimization *** formulating the problem of enhancing the motion stability of the hexapod robot as a Quadratic Programming(QP)optimization problem,this approach can effectively address this *** of a hexapod robot using a fault-tolerant gait,along with real field experiments,were conducted to validate the effectiveness and feasibility of the contact force optimization *** results demonstrate that this approach can be used to design a motion controller for a hexapod robot with a significantly improved motion *** summary,the proposed contact force optimization method offers a promising solution for enhancing the motion stability of hexapod robots with single leg failures and has the potential to significantly advance the development of fault-tolerant hexapod robots for various applications.

关键词： Hexapod robot Fault-tolerant Stability margin Contact force optimization

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A trajectory-level robot skill learning method based on fuzzy systems

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Science China(Information Sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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PCE: Multi-Agent Path Finding via Priority-Aware Communication & Experience Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年 1-13页

作者： Gao, Jianqi Li, Yanjie Ye, Zhaohui Wu, Xinyu Department of Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics and School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE

关键词： Aggregates

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Learning Agile Quadrotor Flight in Restricted Environments with Safety Guarantees

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年第9期9卷 1-8页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Wu, Xinyu Department of Control Science and Engineering Harbin Institute of Technology Shenzhen and Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. This paper focuses on the safety issue of Reinforcement Learning (RL)-based control for agile quadrotor flight in restricted environments. To this end, we propose a unified Adaptive Safety Predictive Corrector (ASPC) to certify each output action of the RL-based controller in real-time, ensuring its safety while maintaining agility. Specifically, we develop the ASPC as a finite-horizon optimal control problem, formulated by a variant of Model Predictive Control (MPC). Given the safety constraints determined by the restricted environment, the objective of minimizing loss of agility can be optimized by reducing the difference between the actions of RL and ASPC. As the safety constraints are decoupled from the RL-based control policy, the ASPC is plug-and-play and can be incorporated into any potentially unsafe controllers. Furthermore, an online adaptive regulator is presented to adjust the safety bounds of the state constraints with respect to the environment changes, extending the proposed ASPC to different restricted environments. Finally, simulations and real-world experiments are demonstrated in various restricted environments to validate the effectiveness of the proposed ASPC. IEEE

关键词： Reinforcement learning

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FWAF-VID: A Flapping-Wing Aggressive Flight Benchmark Dataset for Visual-Inertial Localization

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IEEE robotics and Automation Letters 2025年第6期10卷 6328-6335页

作者： Jiang, Jizhou Pan, Erzhen Xu, Wenfu Sun, Wei Ye, Jingyang Harbin Institute of Technology School of Robotics and Advanced Manufacture Shenzhen518055 China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China Guangdong Biomimetic Intelligent Unmanned System Engineering Technology Research Center Shenzhen518052 China

Accurate state estimation of micro aerial vehicles (MAVs) in high-speed and dynamic environments poses a significant challenge for visual-inertial odometry (VIO) algorithms. Flapping-wing aerial vehicles (FWAVs), as an emerging flight platform, have attracted significant attention for stealth capabilities and efficient flight characteristics. Despite the availability of numerous MAV visual-inertial datasets for six-degree-of-freedom (6-DoF) state estimation, these datasets are not applicable for FWAVs with pronounced vibrations and agile maneuverability. To address this gap, we propose a large-scale flapping-wing aggressive flight visual-inertial dataset FWAF-VID. It contains diverse integrations of synchronized onboard cameras and IMU sensors. A total of 28 sequences include static flapping, calibration, and real-world flights collected in outdoor and indoor environments. The 17 flight sequences feature variations in illuminations, speeds, trajectories, camera perspectives, and flight modalities. We provide precisely aligned ground truth RTK and UWB measurements for algorithm evaluation. Furthermore, a comprehensive benchmark comparison is conducted, qualitatively and quantitatively evaluating the positioning accuracy of state-of-the-art VIO algorithms. The experimental results indicate that despite the degradation in localization accuracy in high-dynamic environments, FWAF-VID can effectively support the further development of VIO algorithms for FWAVs. To the best of our knowledge, this is the first onboard benchmark dataset tailored for aggressive flight in flapping-wing airborne platforms. © 2025 IEEE.

关键词： Micro air vehicle (MAV)

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Self-Regulating Pre-Tensioning Parameter Strategy for Control of Cable-Driven Knee Exoskeleton

Self-Regulating Pre-Tensioning Parameter Strategy for Contro...

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2024 China Automation Congress, CAC 2024

作者： Han, Jiaqi Yin, Weihao Jing, Zhibo Han, Jianda Zhang, Juanjuan Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information System Nankai University Tianjin300350 China

ISBN: (纸本)9798350368604

Knee exoskeletons can offer additional strength and stability for individuals with mobility impairments by providing proper assistance. However, the precise timing of assistance torque for the knee joint poses a challenge to the control of cable-driven exoskeleton systems. Conventional torque-position switching control with a pre-tensioning strategy often fails to meet the precision requirements. In this paper, we developed a self-regulating pre-tensioning parameter strategy to enhance the control performance of cable-driven knee exoskeletons. A specific knee exoskeleton capable of providing both extension and flexion assistance was selected for study. Through geometric analysis of the human-exoskeleton interaction system, a more accurate kinematic relationship has been established, and a state variable named "tightness" has been introduced to describe the cable state. During exoskeleton-assisted walking, the pre-tensioning parameter is iteratively regulated based on tightness, aiming to bring the cable to a critically-tensioned state at the moment of heel strike. Preliminary experimental results demonstrate the strategy significantly improves control precision, the root-mean-square-error of torque tracking with this strategy are reduced by 88.7% and 77.4% for extension and flexion assistance, respectively, compared to scenarios without pre-tensioning. This enhanced control strategy shows promise for further advancing the capabilities of exoskeletons in facilitating human locomotion. © 2024 IEEE.

关键词： Exoskeleton (robotics)

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TrinityMag:A novel magnetically actuated miniature robot manipulating system with a human-scale workspace

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Science China(Technological Sciences) 2024年第11期67卷 3546-3558页

作者： LI Dong CHEN BinHan HUANG ChenYang XU Sheng WU XinYu XU TianTian Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Key Laboratory of Biomedical Imaging Science and System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

The development of the magnetic manipulating system is essential for applications of magnetically actuated miniature robots in biomedical practice,such as targeted therapy and precise ***,the workspaces of existing magnetic manipulating systems for miniature robots are mostly insufficient to manipulate miniature robots inside human *** present study proposes an innovative electromagnets-based manipulating system,TrinityMag,which can produce dynamic three-dimensional(3D)magnetic fields in a human-scale spherical workspace with a 2.6 m *** magnetic field of a single electromagnet is simulated,and a new calibration technic is designed based on deep learning ***,the arrangement of three electromagnets is optimized to produce maximal 3D arbitrary magnetic fields with limited ***,a target-tracking algorithm is developed so that the TrinityMag can track the miniature robot in real ***,the TrinityMag is validated in experiments to manipulate a soft millirobot to move in human-scale tortuous tracks with two types of *** maximum speed of the soft millirobot reaches 11.05 body length/*** work contributes to a significant increment in the workspace of the electromagnets-based manipulating system for miniature *** further expect that the TrinityMag could push the applications of miniature robots from laboratory to clinical practice.

关键词： magnetic manipulating system human-scale workspace magnetically actuated miniature robots

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Fast-convergent model predictive control of omni-directional mobile robots

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International Journal of systems, Control and Communications 2023年第2期14卷 148-167页

作者： Hu, Yin Zhao, Minghui Zhang, Xuebo Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China

Omni-directional wheeled mobile robots (OWMRs) present high manoeuvrability and can move in all directions of the plane. However, for active-caster-type OWMRs (ACT-OWMRs), satisfying physical constraints of multiple motors is challenging. To guarantee motor constraints and improve the tracking control performance, a new model predictive control (MPC)-based controller termed as ‘MPC-FCR’ is designed, which embeds a real-time fast-convergent trajectory planner to generate high efficient gentle reference trajectory. Such a framework has two main advantages. First, the gentle trajectory generation module is formulated as a constrained optimisation problem, which can achieve fast convergence performance while satisfying the robot constraints. Second, both motor and robot constraints are considered in MPC-FCR control law. The proposed MPC-FCR is implemented to achieve real-time performance within a control period of 20 milliseconds. Experimental results show the superior performance of MPC-FCR in terms of convergence speed and the capability to handle physical constraints, compared with the classical controller. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Model predictive control

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