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Design of a Bio-inspired Extensible Continuum Manipulator with Variable Stiffness

Journal of Bionic Engineering 2025年第1期22卷 181-194页

作者： Dongbao Sui Sikai Zhao Tianshuo Wang Yubin Liu Yanhe Zhu Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001China

This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant ***,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its *** design features two concentric parts:inner pneumatically actuated bellows and an outer tendon-driven helical *** tendons control the omnidirectional bending of the manipulator,while the fusion of the pneumatic bellows with the tendon-driven spring results in an antagonistic actuation mechanism that provides the manipulator with variable stiffness and *** paper presents a new design for extensible manipulator and analyzes its stiffness and motion *** results are consistent with theoretical analysis,thereby demonstrating the validity of the theoretical approach and the versatile practical mechanical properties of the continuum *** impressive extensibility and variable stiffness of the manipulator were further demonstrated by performing a pin-hole assembly task.

关键词： Bioinspired robots Continuum robots Soft robotics Variable stiffness

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PMM-Net: Single-Stage Multi-Agent Trajectory Prediction with Patching-Based Embedding and Explicit Modal Modulation

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IEEE robotics and Automation Letters 2025年第7期10卷 6664-6671页

作者： Huajian, Liu Wei, Dong Kunpeng, Fan Chao, Wang Yongzhuo, Gao Harbin Institute of Technology State Key Laboratory of Robotics and System China

Analyzing and forecasting trajectories of agents like pedestrians plays a pivotal role for embodied intelligent applications. The inherent indeterminacy of human behavior and complex social interaction among a rich variety of agents makes this task more challenging than common time-series forecasting. In this letter, we aim to explore a distinct formulation for multi-agent trajectory prediction framework. Specifically, we propose a patching-based temporal feature extraction module and a graph-based social feature extraction module, enabling effective feature extraction and cross-scenario generalization. Moreover, we reassess the role of social interaction and present a novel method based on explicit modality modulation to integrate temporal and social features, thereby constructing an efficient single-stage inference pipeline. Results on public benchmark datasets demonstrate the superior performance of our model compared with the state-of-the-art methods. The code is available at: https://***/TIB-K330/pmm-net. © 2016 IEEE.

关键词： Signal modulation

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Low-Light Enhancement Visual SLAM via Deep Deformable Power Curve Estimation

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IEEE Sensors Journal 2025年第10期25卷 17404-17412页

作者： Liu, Yanjie Wu, Heng Zhang, Weiwu Wang, Chao Wei, Yanlong Ren, Meixuan Harbin Institute of Technology State Key Laboratory of Robotics and System Department of Mechatronics Engineering Harbin150001 China

The unevenness and darkness of lighting in real environments are one of the main issues that affect the practical application of visual simultaneous localization and mapping (SLAM). To address this issue, we propose a visual SLAM algorithm based on low-light enhancement networks. First, we designed a lightweight low-light enhancement network based on deformable power curves, DPCE-Net, to adjust the pixels’ dynamic range of a low-light image. The curve is derived from power function, which considers the range, monotonicity, and differentiability of pixel values, and has a high dynamic range. DPCE-Net is trained and evaluated without reference images, effectively expanding the application scenarios of low-light enhancement. Then, combine the DPCE-Net with ORB-SLAM2 to construct a low-light enhancement SLAM (DPCE-SLAM). In the low-light image enhancement experiment, we compared with the state-of-the-art method, Enlighten-GAN, and Zero-DEC, achieving the good performance in structural similarity (SSIM), mean square error (mse), peak signal to noise ratio (PSNR), and natural image quality evaluator (NIQE) indicators. In state estimation evaluation, DPCE-SLAM can effectively increase the number of correctly matched feature points in dark environments, while also improving the robustness of state estimation. © 2001-2012 IEEE.

关键词： Gallium nitride

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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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A Novel Filtering Framework for High-Density sEMG Based on Variational Mode Decomposition and Independent Vector Analysis

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IEEE Sensors Journal 2025年第6期25卷 9831-9841页

作者： Zhao, Zeming Guo, Weichao Xia, Miaojuan Sheng, Xinjun Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration The Meta Robotics Institute Shanghai200240 China

During the acquisition process, surface electromyography (sEMG) recordings are unavoidably contaminated by different types of noise signals, including baseline noise (BLN), powerline interference (PLI), and white Gaussian noise (WGN). The inclusion of these noise signals significantly diminishes the quality of sEMG signals and impairs the accuracy and resilience of their subsequent utilization. There are two significant issues concerning existing filters: 1) the primary technique for filters targeting BLN and PLI remains IIR filters. However, this methodology makes it challenging to prevent the filters from suppressing sEMG signals in the stopband and 2) the noise signals that are filtered out by the filters targeting WGN do not adhere to a Gaussian distribution. In this study, we propose a novel filtering framework that combines split spectrum processing (SSP) and mix source separation (MSS) to effectively eliminate the three types of noise signals and address the two aforementioned concerns. In this article, other four well-designed filtering methods, including the infinite impulse response (IIR) filter, ensemble empirical mode decomposition (EEMD) method, variational mode decomposition (VMD) method and the independent vector analysis (IVA) method, were evaluated for comparison. The proposed filtering framework demonstrated superior performance in eliminating all three types of noise signals. The simulated signals showed an improvement in SNR of 29.7, 22.4, and 12.9 dB for sEMG signals corrupted by BLN, PLI, and WGN with input SNRs of -10 dB, respectively. The experimental results indicated that the proposed method achieved an average improvement in SNR of 15.9 dB. The proposed filter is highly effective in eliminating all three types of noise and can be utilized for various applications that necessitate sEMG signals, such as gesture recognition and sEMG decomposition.(Figure presented.) © 2001-2012 IEEE.

关键词： White noise

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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 Harbin150006 China Lanzhou University of Technology Lanzhou730050 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. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Emergency services

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Online Motion Generation via Tangential Sampling-Based MPC Around Nonconvex Obstacles

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IEEE robotics and Automation Letters 2025年第6期10卷 5537-5544页

作者： Zhao, Guangbao Jin, Ninglong Wu, Jianhua Xiong, Zhenhua Institute of Robotics School of Mechanical Engineering State Key Laboratory of Mechanical System and Vibration Shanghai JiaoTong University Shanghai200240 China

Collision-free motion planning has a well-established research history, but the majority of studies have been centered around Euclidean space and conducted offline. The primary challenge in online motion planning lies in circumventing local minima, which become more pronounced in configuration space. We propose an online method for generating collision-free motion in configuration space that effectively avoids local minima. Our approach decomposes the optimal velocity into nominal and tangential components, with the tangential velocity optimized to facilitate escape from local minima. The tangential velocity is defined in the tangential space, with its normal direction determined by the gradient of the nearest distance between the robot and obstacles, relative to the robot's states. Direct optimization of the tangential velocity is challenging due to its dependence on varying tangent spaces. To address this, we represent the tangential velocity using the orthogonal basis of the tangent space, decoupling it from the varying tangent space. This allows explicit optimization of the tangential velocity by optimizing its components. Additionally, we introduce a warm-start operator in the tangent space to ensure the consistency and convergence. Furthermore, we propose a dynamic weight based on proximity to local minima to balance the tangential and nominal velocities, forming the optimal velocity. The effectiveness of our approach in avoiding local minima is validated through simulations and physical experiments. © 2016 IEEE.

关键词： Motion planning

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Mechanism of material removal and chip formation of alumina dispersion strengthened copper in micro-milling

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Frontiers of Mechanical Engineering 2025年第1期20卷 27-43页

作者： Chang LIU Chunya WU Xiguang LI Bo HOU Jiahao WU Ruijiang SUN Mingjun CHEN School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

Alumina dispersion-strengthened copper (ADSC), as a representative particle-reinforced metal matrix composite (PRMMC), exhibits superior wear resistance and high strength. However, challenges arise in their processability because of the non-uniform material properties of biphasic materials. In particular, limited research has been conducted on the reinforcement mechanism and behavior of particles during material cutting deformation of PRMMC with nanoscale particles. In this study, a cutting simulation model for ADSC was established, separating the nanoscale reinforcement particles from the matrix. This model was utilized to analyze the interactions among particles, matrix, and tool during the cutting process, providing insights into chip formation and fracture. Particles with high strength and hardness are more prone to storing stress concentrations, anchoring themselves at grain boundaries to resist grain fibration, thereby influencing the stress distribution in the cutting deformation zone. Stress concentration around the particles leads to the formation of discontinuous chips, indicating that ADSC with high-volume fractions of particle (VFP) exhibits low cutting continuity, which is consistent with the results of cutting experiments. The tool tip that is in contact with particles experiences stress concentration, thereby accelerating tool wear. Cutting ADSC with 1.1% VFP results in tool blunting, which increases the radius of cutting edge from 0.5 to 1.9 μm, accompanied with remarkable coating delamination and wear. Simulation results indicate that the minimum uncut chip thickness increases from 0.04 to 0.07 μm as VFP increases from 0.3% to 1.1%. In conjunction with scratch experiments, MUCT increases with the augmentation of VFP. Computational analysis of the specific cutting force indicates that particles contribute to the material’s size effect. The results of this study provide theoretical guidance for practical engineering machining of ADSC, indicating its g

关键词： alumina dispersion-strengthened copper particle-reinforced metal matrix composites material removal mechanism micro-milling chip formation minimum uncut chip thickness

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A Lower Limb Exosuit for Assisting Knee Joint in Rehabilitation During Walking 11

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

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11th International Conference on Mechatronics and robotics Engineering, ICMRE 2025

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

ISBN: (纸本)9798331509293

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. © 2025 IEEE.

关键词： Neuromuscular rehabilitation

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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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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 Suzhou215123 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 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. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Industrial robots

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