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Simulation and analysis of asteroid force closure anchoring performance based on discrete element method

Chinese Journal of Aeronautics 2023年第8期36卷 381-394页

作者： Tingzhang WANG Qiquan QUAN Hongshuai GAO Mengxue LI Dewei TANG Zongquan DENG State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

Asteroid exploration is significant for studying the origin of the solar system,establishing planetary defenses,and alleviating the resource crisis of the *** anchoring is the basis of in-situ exploration and resource development and ***,the performance of asteroid force-closure anchoring is investigated using the discrete element *** micro parameters of the simulated materials are calibrated with angle of repose and uniaxial compression experiments,based on which the regional modeling method is adopted to establish the anchoring discrete element *** anchoring experiments are conducted on a self-developed microgravity simulation platform to verify the accuracy of the simulation *** asteroid anchoring simulations are performed to investigate the influence of external force on the anchoring *** analysis of anchoring force varying with time and the interaction between the anchor and regolith particles reveals the influence mechanism of external force direction on the anchoring *** external force direction affects the critical anchoring force by influencing the failure of the force-closure *** comprehensive analysis of simulation results clarifies the variation of the critical anchoring force with the external ***,a stable anchoring region is established,beneficial for asteroid anchoring device design.

关键词： Anchoringforce Asteroid exploration Discrete element method Force closureanchoring Simulationverification

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Hybrid Static-dynamic Sensation Electrotactile Feedback for Hand Prosthesis Tactile and Proprioception Feedback

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Journal of Bionic Engineering 2023年第1期20卷 267-277页

作者： Bin Yang Li Jiang State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001China

Tactile and proprioception feedback are essential to myoelectric hand prostheses control for regaining functionality of lost hands of *** studies focus on tactile feedback,while the lack of appropriate multisensory feedback,especially proprioception feedback,limits the grasping ***,a typical non-invasive stimulation scheme for sensation feedback uses stimulation on the stationary site of the skin continuously,which can lead to fatigue and adaptation of sensation,further reduces the feedback consistency,and increases the cognitive burden for the *** the sensitivity and modality matching of sensation,this study presented a multimodal sensations feedback scheme based on hybrid static-dynamic sensation elicited by multisite Transcutaneous Electrical Nerve Stimulation(TENS)to deliver grasping force and joint position *** the proposed scheme,stimulation of single electrode produced only in-loco tactile sensation under the electrode,and the sensation intensity was adjusted according to grasping force;sequential activation of multi-electrodes produced an illusion dynamic sensation of a stimulus moving,and the velocity and direction of movement were adjusted according to finger joint *** test results demonstrated the identifiability of stimulus in the proposed ***,prosthetic hand closed-loop grasping tasks evaluate the effectiveness of the proposed feedback *** results showed that the proposed feedback scheme could substantially improve the grasping accuracy and *** addition,the study outcomes also demonstrated the benefit of artificial proprioception feedback in grasping rapidity and security.

关键词： TENS-Prosthetic hand control-Bioinspired sensation-Multimodal sensations Proprioception feedback Tactilefeedback Myoelectric control

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A policy iteration method for improving robot assembly trajectory efficiency

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Chinese Journal of Aeronautics 2023年第3期36卷 436-448页

作者： Qi ZHANG Zongwu XIE Baoshi CAO Yang LIU State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

Bolt assembly by robots is a vital and difficult task for replacing astronauts in extravehicular activities(EVA),but the trajectory efficiency still needs to be improved during the wrench insertion into hex hole of *** this paper,a policy iteration method based on reinforcement learning(RL)is proposed,by which the problem of trajectory efficiency improvement is constructed as an issue of RL-based objective ***,the projection relation between raw data and state-action space is established,and then a policy iteration initialization method is designed based on the projection to provide the initialization policy for *** iteration based on the protective policy is applied to continuously evaluating and optimizing the action-value function of all state-action pairs till the convergence is *** verify the feasibility and effectiveness of the proposed method,a noncontact demonstration experiment with human supervision is *** results show that the initialization policy and the generated policy can be obtained by the policy iteration method in a limited number of demonstrations.A comparison between the experiments with two different assembly tolerances shows that the convergent generated policy possesses higher trajectory efficiency than the conservative *** addition,this method can ensure safety during the training process and improve utilization efficiency of demonstration data.

关键词： Bolt assembly Policy initialization Policy iteration Reinforcement learning(RL) Robotic assembly Trajectory efficiency

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Leader-follower:Human-centered intention-guided controller for novel SuperLimb with application to load-carrying scenarios

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Science China(Technological Sciences) 2025年第1期68卷 321-334页

作者： Qinghua ZHANG Xianglong LI Hongwei JING Kerui SUN Yuancheng LI Sikai ZHAO Lele LI Haotian JU Ziqi WANG Rui WU Tianjiao ZHENG Jie ZHAO Yanhe ZHU The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China The Learning Algorithms and Systems Laboratory School of EngineeringÉcole Polytechnique Fédérale de LausanneLausanne CH 101510587Switzerland

Supernumerary robotic arms(SuperLimb)are a new type of wearable robot that works closely with humans as a third hand to augment human operation *** conveyance of wearers'intentions,allocation of roles,and humancentered interaction considerations are the key points in the process of human-SuperLimb *** paper proposes a human-centered intention-guided leader-follower controller that relies on the dynamic modeling of SuperLimb with application to load-carrying *** proposed leader-follower controller takes the human as the leader and the SuperLimb as the follower,achieving effective information communication,autonomous coordination,and good force compliance between SuperLimb,humans,and the environment under human safety ***,the human-SuperLimb dynamic system is modeled to achieve force interaction with the environment and ***,to achieve the precise intention extraction of humans,pose data from five visual odometry sensors are fused to capture the human state,the generalized position,the velocity of hands,and the surface electromyography signals from two myoelectric bracelets sensors are processed to recognize the natural hand gestures during load-carrying scenarios by a designed Swin transformer ***,based on the real-time distance detection between human and mechanical limbs,the security assurance and force-compliant interaction of the human-SuperLimb system are ***,the human hand muscle intention recognition,human-robot safety strategy verification,and comparative load-carrying experiments with and without the proposed method are conducted on the SuperLimb *** showed that the task parameters are well estimated to produce more reasonable planning trajectories,and SuperLimb could well understand the wearer's intentions to switch different SuperLimb *** proposed sensor-based human-robot communication framework motivates future studies of other collaboration scenes fo

关键词： SuperLimb leader-follower human intention estimation human-robot safety human-robot communication

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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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Development of a novel hand-eye calibration for intuitive control of minimally invasive surgical robot

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Frontiers of Mechanical Engineering 2022年第3期17卷 91-108页

作者： Yanwen SUN Bo PAN Yili FU State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin150001China

Robotic-assisted surgical system has introduced a powerful platform through dexterous instrument and hand-eye coordination intuitive *** knowledge of laparoscopic vision is a crucial piece of information for robot-assisted minimally invasive surgery focusing on improved surgical *** the transformation with respect to the laparoscope and robot slave arm frames using hand-eye calibration is essential,which is a key component for developing intuitive control *** proposed a novel two-step modified dual quaternion for hand-eye calibration in this *** dual quaternion was exploited to solve the hand-eye calibration simultaneously and powered by an iteratively separate *** obtained hand-eye calibration result was applied to the intuitive control by using the hand-eye coordination *** simulations and experimental studies were conducted to evaluate the proposed method on our surgical robot *** extensively compared the proposed method with state-of-the-art *** demonstrate this method can improve the calibration *** effectiveness of the intuitive control algorithm was quantitatively evaluated,and an improved hand-eye calibration method was *** relationship between laparoscope and robot kinematics can be established for intuitive control.

关键词： minimally invasive surgery hand-eye calibration intuitive control surgical robot dual quaternion

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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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Magnetic-Field-Assisted LCD Stereolithography for Centipede-Inspired Magnetic Soft Robot

Magnetic-Field-Assisted LCD Stereolithography for Centipede-...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wang, Jinrong Li, Ruixuan Xu, Yaoyuan Li, Shishi Meng, Xianghe Xie, Hui State key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9781665481090

This paper presents a novel magnetic-field-assisted LCD stereolithography technique for fabricating centipede-inspired magnetic soft robots. Unlike previous DLP-based methods, our approach leverages Liquid Crystal Display (LCD) technology, offering a simpler optical path, comparable resolution, and cost-effectiveness. The method integrates LCD photo-polymerization with a permanent magnet orienting system possessing 5-DOF in motion, enabling precise control over the direction of magnetization patterns during manufacturing. We demonstrate the technique by designing and fabricating a biomimetic centipede robot with programmable deformation capabilities. Finite element analysis was used to simulate the robot's deformation behavior, which was subsequently validated through experimental locomotion tests. The fabricated robot exhibited complex deformation and efficient locomotion in response to external magnetic fields. This approach advances the creation of intricate magnetic arrangements for planar soft robots, potentially expanding their application in fields such as biomedicine and microfluidics. The proposed method provides a new pathway for manufacturing biologically inspired magnetic soft robots with complex programmable behaviors. © 2024 IEEE.

关键词： Liquid crystal displays

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Deep Learning-Enhanced Super-Resolution Ultrasound for Efficient Brain Vascular Mapping

Deep Learning-Enhanced Super-Resolution Ultrasound for Effic...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Sun, Andi Shen, Xingjian Meng, Xianghe Xie, Hui Harbin Institute of Technology State key Laboratory of Robotics and Systems Harbin150080 China

ISBN: (纸本)9781665481090

Robotic implantation of neural electrodes for in-vasive brain-computer interface(BCI) requires precise vascular mapping to avoid major blood vessels. While super-resolution ultrasound imaging offers superior resolution compared to traditional methods, it typically requires probes with numer-ous elements, demanding substantial hardware resources. This paper presents a novel approach combining deep learning with reduced-element probes for high-resolution vascular imaging. The proposed method employs a transformer-based neural network to accurately localize high-density microbubbles while reducing the required number of probe elements. Simulations reveal that a 32-element linear probe with deep learning outper-forms a 64-element probe using 2D normalized cross-correlation for microbubble concentrations below 1.95 microbubbles/mm2. The overall localization precision and Jaccard index demon-strate superior performance of the deep learning approach, particularly at lower microbubble densities. In vivo experiments on a mouse brain model using a 64-element probe (15 MHz) and deep learning achieved vascular network reconstruction with 21 um resolution, distinguishing vessels 26 um apart. This technique significantly lowers the hardware requirements for constructing high-resolution vascular networks, thereby providing detailed cerebrovascular distribution maps. These maps have the potential to enable more precise planning and safer execution of neural electrode implantation for BCI research, while reducing overall system complexity. © 2024 IEEE.

关键词： Brain mapping

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Position-aware pushing and grasping synergy with deep reinforcement learning in clutter

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CAAI Transactions on Intelligence technology 2024年第3期9卷 738-755页

作者： Min Zhao Guoyu Zuo Shuangyue Yu Daoxiong Gong Zihao Wang Ouattara Sie Intelligent Robotics Laboratory Faculty of Information TechnologyBeijing University of TechnologyBeijingChina Beijing Key Laboratory of Computational Intelligence and Intelligent Systems BeijingChina Laboratory of Biomechatronics and Intelligent Robotics(BIRO) Department of Mechanical and Aerospace EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA

The positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in *** effectively perform grasping and pushing manipu-lations,robots need to perceive the position information of objects,including the co-ordinates and spatial relationship between objects(e.g.,proximity,adjacency).The authors propose an end-to-end position-aware deep Q-learning framework to achieve efficient collaborative pushing and grasping in ***,a pair of conjugate pushing and grasping attention modules are proposed to capture the position information of objects and generate high-quality affordance maps of operating positions with features of pushing and grasping *** addition,the authors propose an object isolation metric and clutter metric based on instance segmentation to measure the spatial re-lationships between objects in cluttered *** further enhance the perception capacity of position information of the objects,the authors associate the change in the object isolation metric and clutter metric in cluttered environment before and after performing the action with reward function.A series of experiments are carried out in simulation and real-world which indicate that the method improves sample efficiency,task completion rate,grasping success rate and action efficiency compared to state-of-the-art end-to-end *** that the authors’system can be robustly applied to real-world use and extended to novel *** material is available at https://***/NhG\_k5v3NnM}{https://***/NhG\_k5v3NnM.

关键词： deep learning deep neural networks intelligent robots

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