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International Conference on Biomimetic Intelligence and robotics & Medical robotics Forum, ICBIR+MRF 2024

作者： Shi, Juntian Guo, Weichao Sheng, Xinjun State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China

Laser centerline extraction is a critical step in the machine vision-aided measurement process, especially in the field of aerospace drilling and riveting. We propose a novel and efficient algorithm for the extraction of multiple laser centerlines, which consists of three major parts: laser linewidth estimation, ROI (Region of Interest) extraction, and precise positioning. In the linewidth estimation part, a method based on second-order moment is used to estimate the linewidth, and the scanning frame to linewidth ratio is adopted as the convergence condition to achieve a stable estimation result. In the ROI extraction part, we use a scanning frame to perform raster scanning on the entire image, and calculate the feature function threshold based on the sampling and grayscale volume method to complete ROI extraction. In the precise positioning part, we employ an improved method based on the Hessian matrix to reduce computation time, and use a λ filtering method to eliminate noise. Finally, the K-means method is used to classify the center points belonging to different laser centerlines, and RANSAC is utilized to perform line fitting. The final results demonstrate that the proposed algorithm has certain improvements in accuracy and also exhibits high computational efficiency. © 2024 The Authors.

关键词： Linewidth

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"Volume Transfer": A New Design Concept for Fabric-Based Pneumatic Exosuits

arXiv

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arXiv 2024年

作者： Liu, Chendong Yang, Dapeng Chen, Jiachen Dai, Yiming Jiang, Li Liu, Hong Liu, C. Yang, D. Chen, J. Dai, Y. Jiang, L. Liu, H. State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

The fabric-based pneumatic exosuit is now a hot research topic because it is lighter and softer than traditional exoskeletons. Existing research focused more on the mechanical properties of the exosuit (e.g., torque and speed), but less on its wearability (e.g., appearance and comfort). This work presents a new design concept for fabric-based pneumatic exosuits: "Volume Transfer", which means transferring the volume of pneumatic actuators beyond the garment's profile to the inside. This allows for a concealed appearance and a larger stress area while maintaining adequate torques. In order to verify this concept, we develop a fabric-based pneumatic exosuit for knee extension assistance. Its profile is only 26mm and its stress area wraps around almost half of the leg. We use a mathematical model and simulation to determine the parameters of the exosuit, avoiding multiple iterations of the prototype. Experiment results show that the exosuit can generate a torque of 7.6Nm at a pressure of 90kPa and produce a significant reduction in the electromyography activity of the knee extensor muscles. We believe that "Volume Transfer" could be utilized prevalently in future fabric-based pneumatic exosuit designs to achieve a significant improvement in wearability. Copyright © 2024, The Authors. All rights reserved.

关键词： Pneumatic actuators

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Fast-Poly: A Fast Polyhedral Framework For 3D Multi-Object Tracking

arXiv

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arXiv 2024年

作者： Li, Xiaoyu Liu, Dedong Wu, Yitao Wu, Xian Zhao, Lijun Gao, Jinghan State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China

3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues with accuracy and latency consistency. In this paper, we propose Fast-Poly, a fast and effective filter-based method for 3D MOT. Building upon our previous work Poly-MOT, Fast-Poly addresses object rotational anisotropy in 3D space, enhances local computation densification, and leverages parallelization technique, improving inference speed and precision. Fast-Poly is extensively tested on two large-scale tracking benchmarks with Python implementation. On the nuScenes dataset, FastPoly achieves new state-of-the-art performance with 75.8% AMOTA among all methods and can run at 34.2 FPS on a personal CPU. On the Waymo dataset, Fast-Poly exhibits competitive accuracy with 63.6% MOTA and impressive inference speed (35.5 FPS). The source code is publicly available at https://***/lixiaoyu2000/FastPoly. © 2024, CC BY-NC-SA.

关键词： Object detection

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Enhancing Household Service Robots with a Dual-Arm Mobile Manipulator and Multimodal Large Language Models

Enhancing Household Service Robots with a Dual-Arm Mobile Ma...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Liu, Yang Zhao, Yanchao Guo, Weichao Sheng, Xinjun Ding, Han School of Mechanical Engineering Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

This research aims to enhance the practicality of household service robots by integrating multimodal large language models (MLLMs). Utilizing a dual-arm mobile manipulator platform, our focus is on advancing autonomous mobile manipulation in home environments. By leveraging the advanced text understanding and visual processing capabilities inherent in MLLMs, the proposed system adeptly converts user dialogues and environmental visual inputs into precise robotic plans. Among the suite of tested models, GPT-4o mini and Gemini 1.5 flash perform exceptionally well in generating accurate robotic plans. These results underscore a significant enhancement in the robot's ability to manipulate objects within complex home environments, thereby contributing to more seamless human-robot interactions and markedly improved task execution. We anticipate that our findings will inspire future advances in the field of human-robot interaction for home robots. © 2024 IEEE.

关键词： Human robot interaction

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Transformer-Enhanced Motion Planner: Attention-Guided Sampling for state-Specific Decision Making

arXiv

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arXiv 2024年

作者： Zhuang, Lei Zhao, Jingdong Li, Yuntao Xu, Zichun Zhao, Liangliang Liu, Hong The State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Sampling-based motion planning (SBMP) algorithms are renowned for their robust global search capabilities. However, the inherent randomness in their sampling mechanisms often result in inconsistent path quality and limited search efficiency. In response to these challenges, this work proposes a novel deep learning-based motion planning framework, named Transformer-Enhanced Motion Planner (TEMP), which synergizes an Environmental Information Semantic Encoder (EISE) with a Motion Planning Transformer (MPT). EISE converts environmental data into semantic environmental information (SEI), providing MPT with an enriched environmental comprehension. MPT leverages an attention mechanism to dynamically recalibrate its focus on SEI, task objectives, and historical planning data, refining the sampling node generation. To demonstrate the capabilities of TEMP, we train our model using a dataset comprised of planning results produced by the RRT*. EISE and MPT are collaboratively trained, enabling EISE to autonomously learn and extract patterns from environmental data, thereby forming semantic representations that MPT could more effectively interpret and utilize for motion planning. Subsequently, we conducted a systematic evaluation of TEMP's efficacy across diverse task dimensions, which demonstrates that TEMP achieves exceptional performance metrics and a heightened degree of generalizability compared to state-of-the-art SBMPs. Copyright © 2024, The Authors. All rights reserved.

关键词： Motion planning

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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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Optimization method for operation configuration of space manipulator for on-orbit assembly 24

Optimization method for operation configuration of space man...

引用

4th International Conference on Control and Intelligent robotics, ICCIR 2024

作者： Li, Mengfei Liu, Yang Feng, Weichao Cao, Baoshi Xie, Zongwu Xie, Yuteng Li, Chongyang Guo, Chuangqiang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China School of Resources and Environment Northeast Agricultural University Harbin150006 China Agile Robots Beijing Beijing100192 China

ISBN: (纸本)9798400709937

Aiming at the insertion requirements of large space structures during the on-orbit assembly process, a redundant manipulator operation configuration selection method using joint angle variation as a performance evaluation index is proposed, which achieves operation configuration optimization among multiple sets of inverse solutions. At the same time, the risk of collision during installation is reduced. Firstly, the joint angle parameterization method is used to solve all feasible solutions of the redundant manipulator. Then, trapezoidal velocity planning is employed to analyse the operation configuration after the end effector of the manipulator moves a certain distance in different directions of the coordinate system, and the joint weight coefficient is introduced to calculate the weighted value of the angle variation. Finally, select the operation configuration corresponding to the minimum weighted value as the initial configuration for the manipulator. The calculation results show that this method can select an effective solution that satisfies the posture constraints from multiple sets of inverse solutions, giving full play to the redundant characteristics of the SSRMS-type manipulator and ensuring the safety and reliability of the on-orbit assembly process. © 2024 Copyright held by the owner/author(s).

关键词： Inverse kinematics

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Robot Design of Frogs Jumping Based on Soft-Body Detonation Drive

SSRN

引用

SSRN 2023年

作者： Xu, Weibin Pan, Yitao Ma, Weiliang Gao, Feng Liu, Gangfeng Zhao, Jie Fan, Jizhuang Harbin China State Key Laboratory of Robotics and System China

To achieve a strong instantaneous burst jumping ability, a soft body detonation actuator is proposed by combining the advantages of silicone materials and the characteristics of hydrogen and oxygen mixed gas detonation, which can not only enable the robot to exert the superior movement characteristics of the hindlimbs of frogs during jumping but also make its hindlimb structure more dexterous, lightweight and simple. At the same time, a spring-based forelimb mechanism is also designed so that the robot has the function of jumping with multiple attitude angle changes and the function of smooth buffer landing when jumping. Then, the kinematics and jumping efficiency models are established by using the D-H parameter method and geometric method and verified to analyze the optimal jump-out efficiency. Finally, the experimental results prove that the robot can not only achieve 6 consecutive jumps with a single jump reaching a height of 0.6 m and a distance exceeding 1.2 m, but can also easily cross a rectangular obstacle that has a length of 40 cm, a width of 30 cm, and a height of 25 cm. © 2023, The Authors. All rights reserved.

关键词： Robots

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S2H-GNN: Learning Soft to Hard Feature Matching with Sparsified Graph Neural Network

S2H-GNN: Learning Soft to Hard Feature Matching with Sparsif...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Tao Xie Ruifeng Li Zhiqiang Jiang Kun Dai Ke Wang Lijun Zhao Shuozhan Li State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Fujian (Quanzhou)-HIT Research Institute of Engineering and Technology Quanzhou China

In this work, we introduce a soft-to-hard network (S2H-GNN) for precise local feature matching between image pairs. The core of S2H-GNN is a weighted context aggregation algorithm that enables nodes to receive information from their neighbors in order to form a more global understanding. S2HGNN leverages a sparsified graph neural network to enhance the features, consisting of the following modules alternately: (1) Inducing Point Initial Module that uses cosine correlation to identify highly scored keypoints as Inducing points. (2) Message Passing Module that integrates the features of original keypoints into those of Inducing points, which are further leveraged to exchange messages through self attention and cross attention. (3) Attention Upsample Module that propagates the feature of Inducing points to that of original keypoints, obtaining discriminative feature representation. Additionally, we propose an assignment layer to obtain a soft assignment matrix, which views feature matching as a graphy matching problem. Finally, we introduce a novel gap loss to guide S2H-GNN in learning a discriminative cognition of matching and non-matching keypoints, ultimately obtaining the hard assignment matrix. Experimental results demonstrate that S2H-GNN achieves comparable or higher performance in image matching and homography estimation tasks.

关键词：

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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