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42nd Chinese Control Conference, CCC 2023

作者： Cao, Fengkui Li, Chi Wang, Ting State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China College of Information Engineering Dalian University Dalian China Faculty of Robot Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9789887581543

Robust Place recognition is an open challenging problem under various perceptual conditions, e.g., all weather, times-of-day and seasons shifts. Although LiDAR sensors do not suffer from illumination problem of visual appearance, they are dramatically affected by structural changes across seasons. In this paper, a simple yet effective place recognition method is proposed based on phase congruency to achieve long-term robust localization under severe seasonal changes. To improve the efficiency while retaining geometric information of scene layouts in 3D space, a compact cylindrical description is designed to convert 3D point clouds to 2D images, in which the pixel values are computed based on geometric information rather than heights or numbers of points. Then the histogram of orientated phase congruency are encoded as global descriptor for place retrieval. Extensive real experiments on across-season Oxford RobotCar dataset show that the proposed system outperforms baseline methods, verifying its robust performance in challenging scenarios. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Image enhancement

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A New Workspace and Structural Parameter Optimization Method of Parallel Robot 18

A New Workspace and Structural Parameter Optimization Method...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zhang, Haiyun Hu, Weijun Zhang, Renge Wang, Jin Lu, Guodong School of Robotics Ningbo University of Technology Ningbo315211 China Robotics Institute of Zhejiang University Hangzhou310027 China Zhejiang Qiantang Robot and Intelligent Equipment Reserch Co. Ltd Hangzhou310018 China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China

ISBN: (纸本)9798350312201

The parallel robot workspace refers to the set of points and boundary that can be reached by the parallel mechanism. With the continuous development and industrial application of parallel robots, the workspace analysis and optimization becomes a critical link in this process. In this paper, a workspace solution approach based on seed space segmentation and principal component analysis is proposed. In order to improve the working performance of parallel robots, a flexible workspace evaluation method based on quadratic fourth moment is proposed, and a relationship model between flexible workspace and structural parameters is established. Furthermore, based on the multi-objective genetic algorithm, the structure parameters of the parallel robot are optimized by the workspace and flexible workspace indexes. Finally, the advantage and effectiveness of proposed method are verified by experiment and comparison with traditional methods. © 2023 IEEE.

关键词： Principal component analysis

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A kinematic calibration method for robots based on the PGTF error model and Levenberg-Marquardt algorithm 18

A kinematic calibration method for robots based on the PGTF ...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zheng, Zhi Wang, Jin Zhu, Jun Liu, Luan Zhang, Haiyun Lu, Guodong State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China School of Robotics Ningbo University of Technology Ningbo315211 China Robotics Institute of Zhejiang University Hangzhou310027 China Zhejiang Qiantang Robot and Intelligent Equipment Research Co. Ltd Hangzhou310018 China

ISBN: (纸本)9798350312201

Robots use motors for power output and realize joint motion through reducers and mechanical transmissions, which affect the absolute positioning accuracy. In view of this problem, an error model based on Preprocessing-Geometric-Transmission-Flexibility (PGTF) is proposed and solved by Levenberg-Marquardt algorithm. First, the theoretical kinematic model is established by MD-H model method. Second, the data was pre-processed in dimension upgrade and the robot error identification model was established for geometric error, transmission error and flexible error. Third, Levenberg-Marquardt algorithm was used to find the global convergence solution to realize the identification of error parameters, and the actual robot kinematic model was compensated. Finally, the experiment is carried out on the real robot machine. Through theoretical analysis and verification of real machine data, the average error of kenbei-5kg robot is reduced from 6.8787 mm to 0.1267 mm, the positioning accuracy is improved by 98.16%, the accuracy compensation algorithm is accurate, and the compensation effect is remarkable. © 2023 IEEE.

关键词： Robots

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Time-synchronous-averaging-spectrum based on super-resolution analysis and application in bearing fault signal identification

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2024年第7期25卷 573-585页

作者： Zengle REN Yuan WANG Huiyue TANG Xin'an CHEN Wei FENG Guangdong Provincial Key Laboratory of Construction Robotics and Intelligent Construction Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Shenzhen EBORAIL Technology Co. Ltd.Shenzhen518038China National Supercomputing Center in Shenzhen Shenzhen518055China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China University of Chinese Academy of Sciences Beijing100190China Shenzhen University of Advanced Technology Shenzhen518107China

Time-synchronous-averaging(TSA)is based on the idea of denoising by averaging,and it extracts the periodic components of a quasiperiodic signal and keeps the extracted waveform *** paper studies the mathematical properties of TSA,where three propositions are given to reveal the nature of *** paper also proposes a TSA-spectrum based on super-resolution analysis and it decomposes a signal without using any base *** contrast to discrete Fourier transform spectrum(DFT-spectrum),which is a spectrum in frequency domain,TSA-spectrum is a period-based spectrum,which can present more details of the cross effects between different periodic components of a quasiperiodic ***,a case study is carried out using bearing fault analysis to illustrate the performance of TSA-spectrum,where the rotation speed fluctuation of the shaft is estimated,which is about 0.12 ms *** extracted fault signals are presented and some insights are *** believe that this paper can provide new motivation for TSA-spectrum to be widely used in applications involving quasiperiodic signal processing(QSP).

关键词： Time-synchronous-averaging(TSA) Spectrum Quasiperiodic signal processing(QSP) Super-resolution analysis Bearingfaultdetection

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Tracking Motor Unit Discharges Across Days Based on the Pre-Trained Separation Vectors

Tracking Motor Unit Discharges Across Days Based on the Pre-...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Chen Chen Xiangyang Zhu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China Meta Robotics Institute Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Objective. Decoding motor unit activities from surface electromyography (sEMG) has been demonstrated as a promising technique for human-machine interfacing (HMI) in the past decade. However, the current decoding methods have difficulty tracking motor unit discharges across experiments, limiting the motor unit-based HMI within the intra-trial analysis. This study focused on motor unit decoding across multi-days and aimed to demonstrate the feasibility of pretrained separation vectors for motor unit tracking. Methods. One subject participated in the experiment that lasted five days and performed the isometric elbow flexion at four contraction levels daily. The high-density sEMG signals of 64 channels were recorded from the biceps brachii and decomposed into motor unit spike trains (MUSTs) based on the convolutional kernel compensation algorithm. The separation vectors were kept to decompose the sEMG signals in the subsequent days. The multichannel motor unit action potential (MUAP) waveforms were extracted and compared to validate the tracking performance across days. Main results. On average, 20±6 MUSTs were identified from each contraction intensity, among which 3±2 MUSTs were successfully tracked across five days. The MUSTs tracked across 2–4 days were l0±4, 6±4, and 4±3. Conclusion and Significance. These results indicate the feasibility of motor unit tracking across multiple days based on the pretrained separation vectors, extending the potential applications of neural decoding in HMI.

关键词： Source separation Limiting Surface discharges Human-machine systems Motors Vectors Discharges (electric) Decoding Kernel Robots

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GNN-Assisted BiG-AMP: Joint Channel Estimation and Data Detection for Massive MIMO Receiver

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4631-4646页

作者： Liu, Zishen Wu, Nan He, Dongxuan Yuan, Weijie Li, Yonghui Quek, Tony Q. S. School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of System Design and Intelligent Manufacturing Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China School of Electrical and Information Engineering The University of Sydney SydneyNSW2008 Australia Singapore University of Technology and Design 487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of

In this paper, we develop a graph neural network (GNN)-assisted bilinear inference approach to enhance the receiver performance of the MIMO system through message passing-based joint channel estimation and data detection (JCD). Specifically, based on the bilinear generalized approximate message passing (BiG-AMP) framework and conditional correlation of signal, we propose a GNN-assisted BiG-AMP (GNN-BiGAMP) approach, which integrates a GNN module into the data-detection-loop to compensate the inaccurate marginal likelihood approximation. By leveraging the coupling between the channel and received symbols, a bilinear GNN-assisted BiG-AMP (BiGNN-BiGAMP) JCD receiver is further proposed. This method incorporates two GNNs with similar graph representation into the bilinear posterior estimation loops, which not only compensates for approximation errors but also alleviates performance loss due to premature variance convergence, thereby enhancing the receiver performance significantly. To fully exploit the supervised information from channel estimation and data detection, we propose a multitask learning based training scheme, which coordinates GNNs with different tasks in two loops. Simulation results show that our proposed GNN-assisted JCD receivers significantly outperform other JCD counterparts in terms of both channel estimation and data detection. © 2025 IEEE. All rights reserved.

关键词： Graph neural networks

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic system

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Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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H3e: Learning Air Combat with a Three-Level Hierarchical Framework Embedding Expert Knowledge

SSRN

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SSRN 2023年

作者： Qian, Chenxu Zhang, Xuebo Li, Lun Zhao, Minghui Fang, Yongchun Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University China

Learning to perform air combat autonomously has been a long-standing challenge. The design of intelligent game strategies was difficult due to complex dynamic constraints and long decision-making process. Most exiting approaches depend heavily on simplified aircraft models or complex handcrafted rules. Different from previous works, this paper presents H3E, a novel and efficient Three-level Hierarchical decision framework embedding Expert knowledge, which gives birth to various strategies for high-fidelity one-on-one beyond-visual-range (BVR) air combat game. Inspired by the way pilots make decisions, we build a hierarchical framework to divide the air combat into several sub systems in which each level can perform its own task with much smaller exploration space. In addition, to make full use of the expert knowledge while minimizing its limitation, a novel "Rule-Imitation-Reinforcement" (RIR) training paradigm with an adjustable expert-guidance (AEG) loss function is established, which can increase the exploration efficiency as well as the game win rate. Finally, this work is evaluated in the Intelligent Air Game Simulator (IAGSim), a high-fidelity air combat simulation platform, through a series of games against the state-of-the-art (SOTA) methods. The learning process and game results verify the superior performance of our framework in terms of the exploration efficiency (higher rewards with the same training samples) and win rate (at least 72.9%) compared with the exiting SOTA approaches. © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Zonotope-based fault estimation for Lipschitz nonlinear systems 3

Zonotope-based fault estimation for Lipschitz nonlinear syst...

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2024 3rd International Conference on Aerospace and Control Engineering, ICoACE 2024

作者： Ma, Siyuan Zhang, Wei Jiang, Qiang Gao, Sheng School of Automatic and Electrical Engineering Shenyang Ligong University Shenyang110158 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China China-Portugal Belt and Road Joint Laboratory on Space & Sea Technology Advanced Research Shanghai200120 China

An estimation of fault intervals using a T-N-L structured observer is suggested for Lipschitz nonlinear systems. By augmenting state vectors, the augmentation system and its observer are established, enabling the observer to concurrently estimate fault and system states. The L∞ performance is applied to enhance the resilience of the fault interval estimation to external disturbances and unanticipated inputs. An adequate requirement for the observer design is also presented. The interval estimation of states and faults is ultimately created by using a zonotope. The proposed method exhibits advantages and feasibility when compared to existing simulation techniques. © 2025 institute of Physics Publishing. All rights reserved.

关键词： Nonlinear systems

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Simulation and Experimental Study of Piezoelectric Stack Energy Harvester with Arch Beam Applied to the Railway system

SSRN

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SSRN 2022年

作者： Min, Zhaowei Hou, Chengwei Sui, Guangdong Shan, Xiaobiao Xie, Tao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

As one of the most important modes of transportation, the safety of running vehicles and railway track is significant. It is essential to power sensors that detect and track health in remote areas. The vibration energy of the track structure is enormous and stable, which is not limited by weather factors such as solar and wind power. A new type of arch beam piezoelectric stack energy harvester for railway systems is studied in this paper. Through simulation analysis and experimental verification of the energy harvester, the influences of external resistance, load, pre-pressure, and load frequency on the energy harvesting performance of the piezoelectric energy harvester are discussed. When the frequency is less than 6Hz, the energy capture efficiency is greatly affected by the frequency. When the frequency exceeds 6Hz, the frequency has little effect, and the load dramatically affects the energy capture efficiency. The pre-pressure is not the more significant, the better, but there is an optimal value at 4.5kN. The energy capture circuit can be combined with the supercapacitor to power the sensor, forming a self-power device for real-time monitoring of track health and driving safety. © 2022, The Authors. All rights reserved.

关键词： Arches

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