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Study on wear mechanism of small ball-end grinding wheel and surface integrity of complex component under high-speed machining condition

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Wear 2025年 570卷

作者： Qin, Biao Liu, Henan Cheng, Jian Tian, Jinchuan Sun, Jiangang Chen, Mingjun School of Mechatronics Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou450000 China

The small ball-end fine diamond grinding wheel is well-suited for machining complex components with small curved surface structures, demonstrating high-precision and high-quality machining capabilities. By increasing the speed of the workpiece, the issue of poor grinding performance caused by the small diameter of the ball-end grinding wheel can be effectively overcome. However, this strategy inevitably increases wheel wear and affects surface integrity. To address these challenges, this paper systematically investigates the grinding characteristics of the small ball-end grinding wheel. First, grinding experiments were performed to investigate the influence of workpiece speed, feed rate, and grinding depth on the material removal rate, wheel wear, and surface integrity. Then, the wear mechanism of the grinding wheel was analyzed. The wear modes of the grinding wheel at high workpiece speeds include metal adhesive wear and abrasive grain fracture, which enhance the self-sharpening of the grinding wheel while accelerating its wear. Furthermore, the surface morphology creation mechanism of fused silica under different material removal modes was revealed. Moreover, the correlation between material removal rate and surface roughness caused by wheel wear was revealed. A high-speed grinding strategy was subsequently proposed based on the relationship between the grinding characteristics and grinding parameters of the small ball-end grinding wheel under various grinding conditions. Finally, the feasibility of this grinding strategy was validated through its application to the machining of the complex curved fused silica hemispherical resonator (HSR). Experimental results indicate that under the high workpiece speed condition, the best surface roughness of HSR decreases from 90.5 nm to 62.2 nm, while the maximum grinding wheel wear increases from 9.7 μm to 11.5 μm, with minimal impact on surface integrity. Therefore, the high-speed grinding strategy proposed in this study ho

关键词： Fused silica

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MPC-MF: Multi-Point Cloud Map Fusion Based on Offline Global Optimization for Mobile Robots

MPC-MF: Multi-Point Cloud Map Fusion Based on Offline Global...

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第42届中国控制会议

作者： Haiming Gao Qibo Qiu Shun Zhang Wei Hua Zhiyi Su Xuebo Zhang Research Center for Intelligent transportation Zhejiang Lab Institute of Robotics and Automatic Information System (IRAIS) Tianjin Key Laboratory of Intelligent Robotics (TJKLIR) Nankai University

This paper proposes a Multi-Point Cloud Map Fusion(MPC-MF) approach based on offline global optimization for mobile robots. To realize the effective map fusion of multiple point clouds, an offline global optimization approach is firstly proposed based on self constraint generation and mutual constraint generation. Different from the simple addition of fusing multiple maps to generate final complete map, this work makes use of mutual constraint factors between two adjacent sessions to eliminate inconsistencies in the fused map. Note that the factor generation of mutual constraint and the map fusion of global optimization are main contributions of this work. To evaluate the effectiveness of the proposed map fusion approach, three independent sessions have been collected in a real environment. Experimental results on multi-trajectory fusion and multi-map fusion show superior performance of our proposed approach on eliminating local inconsistencies and realizing effective fusion.

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Protein-Folding Inspired Programmable Control system for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhang, Feng Gu, Yuping Wang, Zebin Yuan, Shuai Yang, Yongliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110106 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China

ISBN: (纸本)9781665481090

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem. © 2024 IEEE.

关键词： Robot programming

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Recognition of Dynamic Grasping Motion through Feature Extraction for Teleoperation 5

Recognition of Dynamic Grasping Motion through Feature Extra...

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5th World Robot Conference Symposium on Advanced robotics and Automation, WRC SARA 2023

作者： Dai, Yanping Chen, Wenyuan Xi, Ning Wang, Wenxue Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Emerging Technologies Institute University of Hong Kong Department of Industrial and Manufacturing Systems Engineering Hong Kong

ISBN: (纸本)9798350307320

Detecting human movement intentions and transmitting human operational capabilities to robots is of great significance for teleoperations. However, the difference in kinematic structure between human hands and robotic manipulators brings difficulties to teleoperation mapping. In this paper, we present an approach to hand grasp recognition and mapping based on feature extraction to drive heterogeneous remote manipulator. The hand grasp data set HUST recorded with a data glove was used for this study. The data were preprocessed and their features were extracted by PCA. A neural network-based classifier was obtained through offline training of human grasping activities. We compared different network models and selected the network with the best performance based on the training time and the task requirements of teleoperation. The experimental results showed that the recognition accuracy of dynamic grasping motion with feature extraction is higher than that without feature extraction and can be up to 97.47%. Finally, we validated the feasibility of this method to tele-operate an Barrett hand through online experiments. Our proposed method provides an effective approach of mapping natural human grasping operations to heterogeneous robotic teleoperation systems. © 2023 IEEE.

关键词： Feature extraction

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HG-CBS Planner: Heuristic Group-based Motion Planning for Multi-robot 18

HG-CBS Planner: Heuristic Group-based Motion Planning for Mu...

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

作者： Liu, Weilong Wang, Jin Zhang, Kewen Yu, Huan Zheng, Zhi 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 College of Mechanical Engineering Zhejiang University of Technology Hangzhou310023 China Robotics Institute of Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798350312201

Multi-Agent Path Finding (MAPF) has been widely studied in the field of artificial intelligence and multi-agent path search, and researchers have made improvements to make such algorithms applicable to actual nonholonomic constrained robots. In this paper, the collision detection is improved by body-occupied collision detection, which improves the efficiency of collision detection. In addition, to solve the problem of low efficiency in centralized search for multi-robot solutions, reasonable grouping is performed to reduce the number of collision nodes expanded in the centralized Conflict-based search(CBS), and feasible results are obtained faster. At the same time, the heuristic multi-robot search based on collision frequency is improved to reduce the search time. Finally, we constructed the trajectory smoothing problem based on the multi-robot path search results and applied the solution to real robot trajectory tracking. Our research provides valuable insights into solving trajectory planning problems for nonholonomic constrained mobile robots in practical scenarios. © 2023 IEEE.

关键词： Motion planning

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Viia-hand: a Reach-and-grasp Restoration system Integrating Voice interaction, Computer vision and Auditory feedback for Blind Amputees

arXiv

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arXiv 2023年

作者： Peng, Chunhao Yang, Dapeng Cheng, Ming Dai, Jinghui Zhao, Deyu Jiang, Li State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China Artificial Intelligence Laboratory Harbin Institute of Technology Harbin150080 China

Visual feedback plays a crucial role in the process of amputation patients completing grasping in the field of prosthesis control. However, for blind and visually impaired (BVI) amputees, the loss of both visual and grasping abilities makes the "easy" reach-and-grasp task a feasible challenge. In this paper, we propose a novel multi-sensory prosthesis system helping BVI amputees with sensing, navigation and grasp operations. It combines modules of voice interaction, environmental perception, grasp guidance, collaborative control, and auditory/tactile feedback. In particular, the voice interaction module receives user instructions and invokes other functional modules according to the instructions. The environmental perception and grasp guidance module obtains environmental information through computer vision, and feedbacks the information to the user through auditory feedback modules (voice prompts and spatial sound sources) and tactile feedback modules (vibration stimulation). The prosthesis collaborative control module obtains the context information of the grasp guidance process and completes the collaborative control of grasp gestures and wrist angles of prosthesis in conjunction with the user's control intention in order to achieve stable grasp of various objects. This paper details a prototyping design (named viia-hand) and presents its preliminary experimental verification on healthy subjects completing specific reach-and-grasp tasks. Our results showed that, with the help of our new design, the subjects were able to achieve a precise reach and reliable grasp of the target objects in a relatively cluttered environment. Additionally, the system is extremely user-friendly, as users can quickly adapt to it with minimal training. Copyright © 2023, The Authors. All rights reserved.

关键词： Computer vision

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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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Unscented Kalman-filter-based sliding mode control for an underwater gliding snake-like robot

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Science China(Information Sciences) 2020年第1期63卷 213-225页

作者： Jingge TANG Bin LI Jian CHANG Aiqun ZHANG State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences

With its strong endurance and high maneuverability, an underwater gliding snake-like robot(UGSR) is a strong potential candidate for aquatic exploration and monitoring. The major feature of the UGSR, which distinguishes it from other snake-like robots, is long range and long operation duration by gliding. This study establishes a gliding motion control system for the UGSR based on a sliding mode controller(SMC). The control system stabilizes the system and suppresses the uncertainties and unknown disturbances. In this strategy, chattering is reduced based on the reaching law method. To circumvent the difficulty of velocity measurements, a nonlinear observer based on an unscented Kalman filter(UKF) is employed for state estimation and random noise handling. The effectiveness of the proposed controller and observer is verified by simulating the UKF-based SMC closed-loop system.

关键词： underwater gliding snake-like robot sliding mode control reaching law nonlinear observer unscented Kalman filter robustness

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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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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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