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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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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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High-precision magnetic field measurement system based on a coherent population trapping magnetometer onboard the SATech-01 satellite

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Science China(Technological Sciences) 2025年第2期68卷 227-242页

作者： Hongbo XUE Wei SONG Haoran ZHAO Yiteng ZHANG Shanzhi YE Jindong WANG Ran TAO Peng SANG Keli CHEN Xingzi BI Bingjun CHENG Bin ZHOU Yongliang XUE Yingying TANG Liu LIU Jinsong LI Xiaocheng ZHU Baoquan LI Jinguo LIU Wen CHEN Xiaofeng ZHANG Yonghe ZHANG Lei LI State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Key Laboratory of Solar Activity and Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Key Laboratory of Electronics and Information Technology for Space Systems National Space Science CenterChinese Academy of SciencesBeijing 100190China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Innovation Academy for Microsatellites Chinese Academy of SciencesShanghai 201304China

On July 27,2022,a high-precision system for measuring the magnetic field based on a coherent population trapping magnetometer(referred to as the CPT system)was launched onboard the Space Advanced Technology demonstration satellite(SATech-01)by a ZK-1A *** payload comprises a scalar coherent population trapping magnetometer(CPTM),triaxial anisotropic magnetoresistance magnetometer(AMRM),and nano star tracker mounted on a non-magnetic telescopic tubular *** configuration enables synchronized measurement of scalar and vector geomagnetic fields,as well as the attitude,making the payload with its compact sensors suitable for applications on miniature satellite *** November 7,2022,the novel telescopic tubular mast was deployed in orbit,extending to a length of 5.28 *** CPTM,an absolute scalar magnetometer with an omnidirectional sensor,is the first China-developed quantum/atomic magnetometer successfully operating in *** orbit,the CPTM has sensitivity of~10 pT/Hz^(1/2) and can automatically operate under complex magnetic field *** difference between the scalar fields obtained using the CPTM and CHAOS model has a mean deviation of -3.73 nT and a standard deviation of 26.11 nT(1σ),without on-orbit calibration or *** miniaturized AMRM has a sensitivity of~0.3 nT/Hz^(1/2) and maintains stable and reliable operation in *** low-power and miniaturized nano star tracker has a measurement uncertainty of 14.23″(1σ)in *** mission has realized the on-orbit technical verification of the integrated and synchronized detection of the vector magnetic field and attitude and fully validated the system’s performance,automation level,and reliability.

关键词： magnetic field measurement system coherent population trapping magnetometer anisotropic magnetoresistance magnetometer nano star tracker non-magnetic telescopic tubular mast satellite

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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...

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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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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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Full-state Physical Mirroring Method of Space Manipulator Based on the Multiple Decoupling Principles 2

Full-state Physical Mirroring Method of Space Manipulator Ba...

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2nd International Conference on Artificial Intelligence, Human-Computer Interaction and robotics, AIHCIR 2023

作者： Yang, Tao Qin, Shize Xu, Fang Deng, Songbo Zhang, Hao Shi, Yan Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Beijing Institute of Precision Mechatronics Controls Laboratory of Aerospace Servo Actuation and Transmission State Key Laboratory of Robotics Chinese Academy of Sciences Beijing China Beijing Institute of Precision Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission PR Beijing China Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics PR Shenyang China

ISBN: (纸本)9798350360363

To achieve the goal of an efficient full-state ground test of a 7DOF space manipulator, the kinematic and dynamical coupling characteristics of space manipulator are investigated, and a mirror test method based on the principle of multiple decoupling is proposed to solve the problem of highly dynamic three-dimensional motion conditions of space manipulator that are difficult to verify by ground simulation. It firstly decouples the space manipulator into a 3dof unit,1dof unit and another 3dof unit combination. It achieves joint load reduction through inter-joint dynamics coupling. Afterwards, it designs an air-floating support device to realize the joint space 7DOF motion, and proposes a constant damping joint dynamics compensation control algorithm to eliminate the dynamics disturbances introduced by inter-joint decoupling. Then, an industrial mirror robot arm with consistent kinematic parameters and a highly dynamic mirror control algorithm are designed to map the joint motion states of the space manipulator to the ground robotic arm, and a ground simulation of the Cartesian space motion state of the space robot arm is realized by decoupling the joint space from the Cartesian space motion. Finally, the ground experiment of target grasping based on the physical mirroring method is designed to realize the high-speed full-state ground experiment verification of complex tasks of space manipulator. © 2023 IEEE.

关键词： Robotic arms

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Whole-Body Constrained Learning for Legged Locomotion via Hierarchical Optimization

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IEEE robotics and Automation Letters 2025年第7期10卷 7460-7467页

作者： Wang, Haoyu Zhou, Ruyi Ding, Liang Liu, Tie Zhang, Zhelin Xu, Peng Gao, Haibo Deng, Zongquan Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin 150001 China

Reinforcement learning (RL) has demonstrated impressive performance in legged locomotion over various challenging environments. However, due to the sim-to-real gap and lack of explainability, unconstrained RL policies deployed in the real world still suffer from inevitable safety issues, such as joint collisions, excessive torque, or foot slippage in low-friction environments. These problems limit its usage in missions with strict safety requirements, such as planetary exploration, nuclear facility inspection, and deep-sea operations. In this paper, we design a hierarchical optimization-based whole-body follower, which integrates both hard and soft constraints into RL framework to make the robot move with better safety guarantees. Leveraging the advantages of model-based control, our approach allows for the definition of various types of hard and soft constraints during training or deployment, which allows for policy fine-tuning and mitigates the challenges of sim-to-real transfer. Meanwhile, it preserves the robustness of RL when dealing with locomotion in complex unstructured environments. The trained policy with introduced constraints was deployed in a hexapod robot and tested in various outdoor environments, including snow-covered slopes and stairs, demonstrating the great traversability and safety of our approach. © 2016 IEEE.

关键词： Robots Safety Legged locomotion Training Foot Torque Adaptation models Stress Dynamics Robustness

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On-orbit assembly control based on model predictive control and load online identification

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Advances in Space Research 2025年第1期76卷 533-550页

作者： Li, Yuntao Xu, Zichun Zhao, Zhiyuan Zhuang, Lei Yang, Xiaohang Ma, Boyu Zhao, Jingdong Liu, Hong State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China

Space manipulator are essential for on-orbit assembly (OOA) tasks. This paper proposes an advanced control framework to address key challenges in Cartesian trajectory tracking and compliant assembly. First, a rigid-body dynamic model of the manipulator is established using CAD model and joint friction identification. A Linear Extended state Observer (LESO) is designed to mitigate system errors by modeling both parametric uncertainties and external disturbances as an extended state. Additionally, the method for selecting parameters of the LESO, along with its convergence proof, is presented. Second, a model predictive control (MPC) algorithm is employed to optimize the Cartesian trajectory of the manipulator in real time. By linearizing the Cartesian space trajectory, the MPC problem is formulated as a QP problem. Solving this QP problem in real-time allows for the optimization of the Cartesian space trajectory, thereby improving the trajectory tracking accuracy in Cartesian space. Finally, online identification of load parameters, sensor zero drift, and temperature drift enables effective compliant assembly control. Extensive experiments validate the proposed methods: (1) The Cartesian trajectory tracking error is maintained below 0.1 mm. (2) After sensor compensation for identified load parameters, zero drift, and temperature drift, the maximum force residual is 0.42 N, and the maximum torque residual is 0.1 N m. © 2025 COSPAR

关键词： Predictive control systems

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Target-driven Object Grasping Method for Mobile Manipulator in Clutter

Target-driven Object Grasping Method for Mobile Manipulator ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Yu, Xinkai Gao, Yongzhuo Dong, Wei Li, Mingyang Liu, Huajian Wang, Chao Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

The demand for mobile manipulator in the military field is strong, but there is no product that can achieve autonomous grasping in a cluttered environment. In this paper, a target-driven grasp pose detection algorithm is proposed, which can be used to detect the grasp pose of a specified target object in a cluttered environment. After that, based on the lightweight requirements of the military, a mobile manipulator platform is built, and the forward and inverse kinematics model of the mobile manipulator is established. At the same time, a vehicle-arm coordination algorithm is designed to make the grasping efficiency higher. Finally, we use the mobile manipulator to perform autonomous grasping in a cluttered environment to verify the system functionality. © 2022 IEEE.

关键词： Manipulators

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Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

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Tsinghua Science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang Cao Peiyu Guan Fengshui Jing Min Tan Junzhi Yu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot *** pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and ***,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are *** is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains ***,the channel information in high-level feature is also not well ***,the performance of grasp detection is *** solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle *** low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature *** a hierarchical fusion guarantees the quality of grasp ***,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective *** such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the ***,an information enhancement module is added before the encoder to reinforce input *** proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

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