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IEEE Transactions on Medical robotics and Bionics 2025年第2期7卷 655-665页

作者： Song, Xiaoyu Liu, Jiaqing Pan, Heng Rao, Haotian Wang, Can Wu, Xinyu Southern University of Science and Technology Shenzhen518055 China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China

In this study, we propose a robust myoelectric intention recognition framework to recognize human locomotion mode and detect irrelevant locomotion intention. The framework is integrated into the control system of the lower limb exoskeleton robot for experimental validation. Most conventional electromyography(EMG) intention detection methods aim to accurately detect the target motion intentions but ignore the possible effects of irrelevant intentions. In traditional action intention recognition strategies, most researchers did not consider entering irrelevant action intentions into the model during training. Therefore, when using a classification model, if irrelevant action intentions are input, the model will still recognize it as a type of target action intention. That can lead to incorrect recognition results, which will cause the robot to perform wrong movements and pose a safety risk to the wearer. To detect and reject irrelevant motion intentions, we first used the dual-purpose autoencoder-guided temporal convolution network (DA-TCN) to obtain discriminative features of the surface EMG signal. Autoencoders (AE)/Variable Autoencoders (VAE) are then trained for each of the seven deep features of the target motion intention. In addition, irrelevant motion intentions are detected according to the value of their reconstruction error. The recall rate of this method for the detection of irrelevant motion intentions exceeds 99% and the accuracy rate exceeds 99%.At the same time, we replaced the TCN with the LSTM model and compared the performance of the two after adding irrelevant motion discrimination. We collected data on seven goals and three unrelated motor intentions from seven experimenters for testing and completed an online experimental validation. The motion recognition accuracy of all the experimenters can be maintained above 86%. © 2018 IEEE.

关键词： Limbs Legged locomotion Exoskeletons Robots Image color analysis Convolution Stairs Training Feature extraction Autoencoders

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Relative Localizability and Localization for Multirobot systems

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IEEE Transactions on robotics 2025年 41卷 2931-2949页

作者： Chen, Liangming Liang, Chenyang Yuan, Shenghai Cao, Muqing Xie, Lihua Southern University of Science and Technology School of System Design and Intelligent Manufacturing Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen518055 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore Carnegie Mellon University Robotics Institute PittsburghPA15213 United States

Inter-robot relative positions are crucial for executing various multirobot missions, such as formation maneuvering and collaborative inspection. However, the current sensing technology usually provides part of relative position information, such as inter-robot distances, bearings and angles. This prompts the study of determining inter-robot relative positions, i.e., relative localization, from these partial measurements. Based on the existing results of static networks' localizability and mobile robots' relative localization, we propose a novel concept, relative localizability to describe whether a multirobot system is relatively localizable. Given each robot's self-displacement measurements and inter-robot partial measurements in d (d ≤ 4) sampling instants, we show that a multirobot system's relative localization can be achieved in a purely algebraic and distributed manner, in which the multirobot system is said to be d-step relatively localizable. To make the results more general, we consider that the multirobot system consists of landmarks, leaders, and followers, and that the inter-robot measurements can be distances, bearings or angles. When robots' coordinate frames have different orientations, we show that the given local measurements can be used to determine robots' relative positions and their coordinate frames' relative orientations simultaneously. Simulations and experiments of relative localization for ground robots are conducted to validate the obtained results. © 2004-2012 IEEE.

关键词： Multipurpose robots

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Mechanical Properties Inside Origami-Inspired Structures: An Overview

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Applied Mechanics Reviews 2025年第1期77卷 011001页

作者： Yan, Peng Huang, Hailin Meloni, Marco Li, Bing Cai, Jianguo Department of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518052 China Harbin Institute of Technology Shenzhen518052 China Key Laboratory of C & PC Structures of Ministry of Education National Prestress Engineering Research Center Southeast University Nanjing211189 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518052 China Key University Laboratory of Mechanism Machine Theory and Intelligent Unmanned Systems of Guangdong Habin Institute of Technology Shenzhen518052 China

In recent decades, origami has transitioned from a traditional art form into a systematic field of scientific inquiry, characterized by attributes such as high foldability, lightweight frameworks, diverse deformation modes, and limited degrees-of-freedom. Despite the abundant literature on smart materials, actuation methods, design principles, and manufacturing techniques, comprehensive reviews focusing on the mechanical properties of origami-inspired structures are relatively rare and unsystematic. This review aims to fill this void by analyzing and summarizing the significant studies conducted on the mechanical properties of origami-inspired structures from 2013 to 2023. We begin with an overview that includes essential definitions of origami, classical origami patterns, and their associated tessellated or stacked structures. Following this, we delve into the principal dynamic modeling method for origami and conduct an in-depth analysis of the key mechanical properties of origami-inspired structures. These properties include tunable stiffness, bistability and multistability, metamechanical properties demonstrated by origami-based metamaterials, and bio-inspired mechanical properties. Finally, we conclude with a comprehensive summary that discusses the current challenges and future directions in the field of origami-inspired structures. Our review provides a thorough synthesis of both the mechanical properties and practical applications of origami-inspired structures, aiming to serve as a reference and stimulate further research. © 2025 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Degrees of freedom (mechanics)

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A Lower Limb Exosuit for Assisting Knee Joint in Rehabilitation During Walking

A Lower Limb Exosuit for Assisting Knee Joint in Rehabilitat...

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Mechatronics and robotics Engineering (ICMRE), International Conference on

作者： Yao Huang Haotian Ju Songhao Guo Tianjiao Zheng Jie Zhao Yanhe Zhu State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798331509293

ISBN: (纸本)9798331509309

For knee rehabilitation patients, it is difficult to maintain balance while walking, and completing a normal gait cycle is challenging. Therefore, we propose a lower limb exosuit tailored for the knee rehabilitation patients to assist in normal walking, and experimentally evaluated the assistance effect of the lower limb exosuit. We mimic the mechanism of the skeletal muscles near the knee joint, by contracting and relaxing the length of the flexible Bowden cable between the thigh and calf, generating assistive torque on the knee joint periodically. We use Inertial Measurement Unit (IMU) to measure lower limb motion parameters, identify gait cycle states, and calculate corresponding plantar pressure and knee joint torque for each phase. We compared surface electromyography (sEMG) signals of three muscle groups (biceps femoris (BF), quadriceps femoris (QF), and gastrocnemius (G)) under conditions of wearing and not wearing the exosuit. The experimental results show that compared to not wearing the exosuit, the mean normalized sEMG signals of the three muscle groups decreased by 4.61 %, 2.41 %, and 3.97% respectively while wearing it, the peak values decreased by 11.60%, 25.69%, and 14.99% respectively, with the quadriceps femoris receiving the highest degree of assistance.

关键词： Knee Legged locomotion Limbs Torque Measurement units Thigh Muscles Pressure measurement Torque measurement Robots

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LSF-planner: a visual local planner for legged robots based on ground structure and feature information

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Autonomous Robots 2025年第2期49卷 1-17页

作者： Zhang, Teng Wang, Xiangji Zha, Fusheng Liu, Fucheng Harbin Institute of Technology The State Key Laboratory of Robotics and System Harbin China Lanzhou University of Technology Lanzhou China

Three-dimensional navigation of legged robots is crucial for field exploration and post-disaster rescue. Existing optimization-based local trajectory planners predominantly focus on obstacle avoidance, neglecting negative obstacles (e.g., pits) and varying ground features (e.g., different terrain types). Additionally, non-overlapping areas between the planned space in three-dimensional trajectory planning and the robot’s actual reachable space lead to decision-making issues between crossing and obstacle avoidance, making it challenging to differentiate between passable and hazardous areas, thus impacting navigation safety and stability. To address these limitations, we propose a novel visual local planner, LSF-Planner (Visual Local Planner for Legged Robots Based on Ground Structure and Feature Information). The LSF-Planner employs a multi-layer local perception map that integrates ground feature semantics, sensor range, and negative obstacles (e.g., voids detected by depth sensors) to construct a ground reliability representation. The Label2Grad method is introduced to convert this representation into gradient layers, incorporating a ground reliability penalty function into trajectory optimization. By incorporating constraints on the center of mass height and crossing angles, LSF-Planner effectively differentiates between traversable and hazardous areas. Experimental results show that LSF-Planner significantly outperforms existing methods in 3D trajectory planning, enhancing the navigation performance of legged robots in unstructured environments.

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Evetac Meets Sparse Probabilistic Spiking Neural Network: Enhancing Snap-Fit Recognition Efficiency and Performance

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IEEE robotics and Automation Letters 2025年第6期10卷 5353-5360页

作者： Fang, Senlin Ding, Haoran Liu, Yangjun Liu, Jiashu Zhang, Yupo Li, Yilin Kong, Hoiio Yi, Zhengkun Faculty of Data Science City University of Macau 999078 China Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China City University of Hong Kong Hong Kong University of Macau 999078 China Shenzhen Institute of Advanced Technology Shenzhen518055 China City University of Macau 999078 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China City University of Macau Faculty of Data Science 999078 China Chinese Academy of Sciences Key Laboratory of Biomedical Imaging Science and System Shenzhen518055 China

Snap-fit peg-in-hole assembly is common in industrial robotics, particularly for 3 C electronics, where fast and accurate tactile recognition is crucial for protecting fragile components. Event-based optical sensors, such as Evetac, are well-suited for this task due to their high sparsity and sensitivity in detecting small, rapid force changes. However, existing research often converts event data into dense images and processing them with dense methods, leading to higher computational complexity. In this letter, we propose a Sparse Probabilistic Spiking Neural Network (SPSNN) that utilizes sparse convolutions to extract features from the event data, avoiding computations on non-zero cells. We introduce the Forward and Backward Propagation Through Probability (FBPTP) method, which enables simultaneous gradient computation across all time steps, eliminating the need for the step-by-step traversal required by traditional Forward and Backward Propagation Through Time (FBPTT). Additionally, the Temporal Weight Prediction (TWP) method dynamically allocates weights for different time outputs, enhancing recognition performance with minimal impact on model efficiency. We integrate the Evetac sensor compactly into our robotic system and collected two datasets, named Tactile Event Ethernet (TacEve-Eth) and Tactile Event Type-C (TacEve-TC), corresponding to cantilever and annular snap-fit structures. Experiments show that the SPSNN achieves the superior trade-off between recognition performance and efficiency compared to other widely used methods, achieving the highest average recognition performance while reducing inference time by over 90% compared to FBPTT-based dense SNN baselines. © 2016 IEEE.

关键词： Robotic assembly

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High-precision trajectory calibration for robot surface machining by meta-heuristic search algorithm from local error in machining area

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The International Journal of Advanced Manufacturing Technology 2025年第5期138卷 2281-2295页

作者： Bi, Guangde Lu, Lei Zhang, Lei Fan, Cheng Sun, Lining School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Industrial robots used in complex surface machining are gradually increasing because of their high flexibility and large workspace. However, due to their low geometric accuracy, their application in high-precision surface machining is hindered. In order to improve the machining accuracy, a high-precision robot trajectory calibration method for complex surface machining is proposed. In the machining process, the machining trajectory is usually only within a certain machining area. In the method, high-precision standard balls are set at the boundary of the machining area. Based on the precise position information of these standard balls, the trajectory of the robot in the machining area is calibrated. Compared with the global robot calibration method, the proposed method can calibrate the robot trajectory in the machining area through standard parts, which will improve the trajectory accuracy of the machining robot to the level of repeated positioning accuracy. In this method, a large amount of standard ball data is obtained by the in-place measuring device before the machining process. Then, based on these data, a meta-heuristic search algorithm is used to calibrate the kinematic deviation of the robot measurement and the machining system. The trajectory of the machining robot is adjusted by the kinematic deviation after calibration, and it is applied to the motion control of the machining process to improve the positioning accuracy of the machining trajectory. In the end, to verify the accuracy and practicability of the machining trajectory obtained by this method, measurement and machining experiments are carried out.

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FSMP: A Frontier-Sampling-Mixed Planner for Fast Autonomous Exploration of Complex and Large 3-D Environments

arXiv

引用

arXiv 2025年

作者： Zhang, Shiyong Zhang, Xuebo Dong, Qianli Wang, Ziyu Xi, Haobo Yuan, Jing Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin China

In this paper, we propose a systematic framework for fast exploration of complex and large 3-D environments using micro aerial vehicles (MAVs). The key insight is the organic integration of the frontier-based and sampling-based strategies that can achieve rapid global exploration of the environment. Specifically, a field-of-view-based (FOV) frontier detector with the guarantee of completeness and soundness is devised for identifying 3-D map frontiers. Different from random sampling-based methods, the deterministic sampling technique is employed to build and maintain an incremental road map based on the recorded sensor FOVs and newly detected frontiers. With the resulting road map, we propose a two-stage path planner. First, it quickly computes the global optimal exploration path on the road map using the lazy evaluation strategy. Then, the best exploration path is smoothed for further improving the exploration efficiency. We validate the proposed method both in simulation and real-world experiments. The comparative results demonstrate the promising performance of our planner in terms of exploration efficiency, computational time, and explored volume. © 2025, CC BY.

关键词： Micro air vehicle (MAV)

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Kirigami-inspired continuum soft arm with embedded sensing for non-destructive inspection and sorting

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Science China Materials 2025年第2期68卷 552-560页

作者： Jinsui Xu Boyi Xu Honghao Yue Yifan Lu Zheping Wang Zongquan Deng Fei Yang State Key Laboratory of Robotics and System School of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China Wu Xianming School of Intelligent Engineering South China University of TechnologyGuangzhou 510641China

The sensing capabilities of a soft arm are ofparamount importance to its overall performance as they allow precise control of the soft arm and enhance its interactionwith the surrounding environment. However, the actuationand sensing of a soft arm are not typically integrated into amonolithic structure, which would impede the arm’s movement and restrict its performance and application scope. Toaddress this limitation, this study proposes an innovativemethod for the integrated design of actuator structures andsensing. The proposed method combines the art of kirigamiwith soft robotics technology. In the proposed method, sensorsare embedded in the form of kirigami structures into actuatorsusing laser cutting technology, achieving seamless integrationwith a soft arm. Compared to the traditional amanogawakirigami and fractal-cut kirigami structures, the proposedmiddle-cut kirigami (MCK) structure does not buckle duringstretching and exhibits superior tensile performance. Based onthe MCK structure, an advanced interdigitated capacitivesensor with a high degree of linearity, which can significantlyoutperform traditional kirigami sensors, is developed. Theexperimental results validate the effectiveness of the proposedsoft arm design in actual logistics sorting tasks, demonstratingthat it is capable of accurately sorting objects based on sensorsignals. In addition, the results indicate that the developedcontinuum soft arm and its embedded kirigami sensors havegreat potential in the field of logistics automation *** work provides a promising solution for high-precisionclosed-loop feedback control and environmental interaction ofsoft arms.

关键词： kirigami embedded sensing continuous soft arm non-destructive inspection

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Development of a Miniature Underactuated Tripod Robot Inspired by Penguin Waddling Gait

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IEEE Transactions on Industrial Electronics 2025年

作者： Liu, Youwei Zhang, Shijing Deng, Jie Li, Jing Liu, Junkao Liu, Yingxiang Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

Mobile robots utilizing vibration direct drive by eccentric motors have the advantages of compact structure, easy control, and low driving voltage, which facilitate miniaturization, lightweight design, and integration. Inspired by the waddling gait of penguins, this work proposes a vibration direct drive miniature tripod robot powered by a single eccentric motor. This robot demonstrates excellent load capacity and low transport costs. Notably, the waddling motion of the robot is achieved by alternately exciting the eccentric motor with positive and negative pulse-width modulation (PWM) signals. An unbalanced force is generated by using the integrated onboard power supply and control system as the eccentric mass of the robot. The structure design and electrical design are conducted, the working principle is analyzed, and a robot prototype is fabricated. The prototype weighs 12 g and has dimensions of 33 mm × 29 mm × 23 mm. Experimental results demonstrate that it can bear a maximum load of 143 g, which is 11.92 times its self-weight, and achieve a minimum cost of transport of 27.98. This work presents a new approach to research vibration direct drive underactuated miniature robots actuated by a single eccentric motor. © 1982-2012 IEEE.

关键词： Mobile robots

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