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IEEE International Conference on robotics and Automation (ICRA)

作者： Jian Chen Mingcong Chen Qingxiang Zhao Shuai Wang Yihe Wang Ying Xiao Jian Hu Danny Tat Ming Chan Kam Tong Leo Yeung David Yuen Chung Chan Hongbin Liu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China Centre of AI and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences (CAIR-HKISI-CAS) HKSAR Department of Biomedical Engineering City University of Hong Kong HKSAR CAIR-HKISI-CAS HKSAR State Key Laboratory of Multimodal Artificial Intelligence Systems CASIA Beijing China Department of Surgery The Chinese University of Hong Kong HKSAR State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China School of Biomedical Engineering and Imaging Sciences King’s College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgical manipulation deep in the brain. Taking into account the uncertainty of the control model, an image-based visual servoing with online robot Jacobian estimation has been implemented to enhance motion accuracy. Furthermore, the application of model predictive control with constraints significantly bolsters the flexible robot’s ability to adaptively track mobile objects and resist external interference. Experimental results underscore that the proposed control system enhances motion stability and precision. Phantom testing substantiates its considerable potential for deployment in neurosurgery.

关键词： Jacobian matrices Visualization Endoscopes Estimation Interference Predictive models Control systems

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A Vision-Based Two-Stage Fruit Outer Diameter Detection Method

A Vision-Based Two-Stage Fruit Outer Diameter Detection Meth...

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IEEE International Conference on robotics and Biomimetics

作者： Yifei Hao Shuaizheng Yan Zhengxing Wu Bingwei He Chenghua Li Junzhi Yu Department of Mechanical Engineering Fuzhou University Fuzhou China Laboratory of Cognitive and Decision Intelligence for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Key Laboratory of Cognition and Decision Intelligence for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Guangzhou Shenghui Cleaning Service Co. Ltd. Guangzhou China Department of Advanced Manufacturing and Robotics State Key Laboratory for Turbulence and Complex Systems BIC-ESAT College of Engineering Peking University Beijing China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Regarding the mobile monitoring system in agricultural automation, the outer diameter monitoring of greenhouse vegetables has significant implications for accurately regulating fruit growth and cultivation plans. In this paper, a novel vision-based two-stage outer diameter detection method is proposed, including the segmentation and outer diameter calculation of greenhouse tomato images. To address the issues of multiple tomatoes in a single image and the similarity in color between tomatoes and the background, a YOLOv8 network embedded with convolutional block attention module is constructed for detection and segmentation in the first stage. Additionally, to solve the problem of inaccurate outer diameter detection caused by different tomato poses and pedicles, a defined central axis method is proposed, which can adaptively filter out the maximum outer diameter candidates and calculate accurate values utilizing depth information in the world coordinate system. The backbone network is fine-tuned on the pre-trained YOLOv8 model with 1000 tomato images. Extensive measurement experiments, involving 215 tomatoes in 80 images, is conducted to validate the effectiveness of our proposed approach. Compared to the ground truth, we obtain a measurement error of 4.27 mm, the coefficient of determination value R2 is 0.9349.

关键词： Image segmentation Measurement errors Adaptation models Automation Image color analysis Robot kinematics Biomimetics Adaptive filters Information filters Monitoring

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Coordinated Guiding Vector Field Design for Ordering-Flexible Multi-Robot Surface Navigation

arXiv

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arXiv 2024年

作者： Hu, Bin-Bin Zhang, Hai-Tao Yao, Weijia Sun, Zhiyong Cao, Ming The School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China The School of Robotics Hunan University Hunan410082 China The Institute of Engineering and Technology University of Groningen Groningen9747 AG Netherlands Department of Electrical Engineering Eindhoven University of Technology Netherlands

We design a distributed coordinated guiding vector field (CGVF) for a group of robots to achieve ordering-flexible motion coordination while maneuvering on a desired two-dimensional (2D) surface. The CGVF is characterized by three terms, i.e., a convergence term to drive the robots to converge to the desired surface, a propagation term to provide a traversing direction for maneuvering on the desired surface, and a coordinated term to achieve the surface motion coordination with an arbitrary ordering of the robotic group. By setting the surface parameters as additional virtual coordinates, the proposed approach eliminates potential singularity of the CGVF and enables both the global convergence to the desired surface and the maneuvering on the surface from all possible initial conditions. The ordering-flexible surface motion coordination is realized by each robot to share with its neighbors only two virtual coordinates, i.e. that of a given target and that of its own, which reduces the communication and computation cost in multi-robot surface navigation. Finally, the effectiveness of the CGVF is substantiated by extensive numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Navigation

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Time-Optimal Trajectory Planning Based on Dynamics for Industrial Robot 5

Time-Optimal Trajectory Planning Based on Dynamics for Indus...

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5th International Conference on Automation, Control and robotics engineering, CACRE 2020

作者： Wang, Rundong Kong, Minxiu Cheng, Yanchun Castellani, Marco Harbin Institute of Technology State Key Laboratory of Robotics and System School of Mechatronics Engineering Harbin China University of Birmingham Department of Mechanical Engineering Birmingham United Kingdom

ISBN: (纸本)9781728198880

Given the trajectory of the industrial robot in Cartesian space, the existing methods only consider the kinematic constraints when optimizing the time trajectory planning, and ignore the maximum driving ability of the motor, which is likely to cause an overrun alarm and greatly reduce the trajectory accuracy. Therefore, this paper studies the time-optimal trajectory planning algorithm based on dynamics. Firstly, the algorithm discretizes the path, calculates the Cartesian coordinates of each discrete point and the differential about the path length. Then, this algorithm considers the constraints of dynamics and kinematics, uses the principle of linear programming, recursively calculates the upper limit value of speed and the maximum acceleration value at each discrete point, and calculates the speed value at each discrete point and keeps it within its allowable ranges. Finally, this algorithm uses the speed to calculate the corresponding time of each discrete point, and according to the interpolation period, outputs the path position of each period, the position and orientation in the Cartesian space and joint parameters. The MATLAB program is written to verify the feasibility and efficiency of the algorithm. © 2020 IEEE.

关键词： Industrial robots

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CylinderTag: An Accurate and Flexible Marker for Cylinder-Shape Objects Pose Estimation Based on Projective Invariants

arXiv

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arXiv 2023年

作者： Wang, Shaoan Zhu, Mingzhu Hu, Yaoqing Li, Dongyue Yuan, Fusong Yu, Junzhi State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China Department of Mechanical Engineering Fuzhou University Fuzhou350000 China National Engineering Laboratory for Digital and Material Technology of Stomatology Center of Digital Dentistry Peking University School Hospital of Stomatology Beijing100190 China

High-precision pose estimation based on visual markers has been a thriving research topic in the field of computer vision. However, the suitability of traditional flat markers on curved objects is limited due to the diverse shapes of curved surfaces, which hinders the development of high-precision pose estimation for curved objects. Therefore, this paper proposes a novel visual marker called CylinderTag, which is designed for developable curved surfaces such as cylindrical surfaces. CylinderTag is a cyclic marker that can be firmly attached to objects with a cylindrical shape. Leveraging the manifold assumption, the cross-ratio in projective invariance is utilized for encoding in the direction of zero curvature on the surface. Additionally, to facilitate the usage of CylinderTag, we propose a heuristic search-based marker generator and a high-performance recognizer as well. Moreover, an all-encompassing evaluation of CylinderTag properties is conducted by means of extensive experimentation, covering detection rate, detection speed, dictionary size, localization jitter, and pose estimation accuracy. CylinderTag showcases superior detection performance from varying view angles in comparison to traditional visual markers, accompanied by higher localization accuracy. Furthermore, CylinderTag boasts real-time detection capability and an extensive marker dictionary, offering enhanced versatility and practicality in a wide range of applications. Experimental results demonstrate that the CylinderTag is a highly promising visual marker for use on cylindrical-like surfaces, thus offering important guidance for future research on high-precision visual localization of cylinder-shaped objects. The code is available at: https://***/wsakobe/CylinderTag. Copyright © 2023, The Authors. All rights reserved.

关键词： Cylinders (shapes)

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Payload Parameters Identification Using Incremental Ensemble Learning

Payload Parameters Identification Using Incremental Ensemble...

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Computer, Control and robotics (ICCCR), International Conference on

作者： Wael Taie Khaled ElGeneidy Ali AL-Yacoub Sun Ronglei School of Mechanical Science and Engineering Huazhong university of science and technology Wuhan China Mechatronics Systems Engineering Department October University for Modern Sciences and Arts Cairo Egypt School of Engineering Coventry University Cairo Egypt EPSRC Centre for Innovative Manufacturing in Intelligent Automation Loughborough University Loughborough U.K. State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350373141

ISBN: (纸本)9798350373158

This paper introduces a new method for identifying the payload inertial parameters for collaborative robots (cobots) that operate in dynamic manufacturing environments with frequent reconfiguration. The proposed method eliminates the need for specific excitation trajectories during the identification process, allowing the identification of payload parameters while the cobot follows any arbitrary task trajectory. This is achieved via an incremental ensemble model, which utilizes incremental neural networks as weak learners. The proposed method successfully adapts the ensemble model to new task paths while maintaining accurate estimations for the payload parameters. The mean absolute error for mass, center of mass, and the moment of inertia parameters were 0.01 kg, 0.0068 kg.m, and 0.0008 kg.m 2 , respectively. These results demonstrate the effectiveness of the model in dealing with new task trajectories in comparison to traditional or batch ensemble models.

关键词： Adaptation models Accuracy Parameter estimation Computational modeling Collaborative robots Data models Trajectory

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Human-in-the-loop Optimization for Adaptive Assist-as-Needed Rehabilitation 12

Human-in-the-loop Optimization for Adaptive Assist-as-Needed...

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Li, Ning Yang, Yang Yang, Tie Chen, Wenyuan Wang, Yihan Yu, Peng Wang, Wenxue Xi, Ning Liu, Lianqing Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of the Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang10016 China School of Electrical and Electronics Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Emerging Technologies Institute Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Pokfulam999077 Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Active voluntary participation in robot-assisted rehabilitation promote the recovery of stroke hemiplegia. However, different patients have personalized recovery states, which needs the adaptive control strategy to improve the patient's participation. Therefore, in this study, a Mirror Adaptive Assist-As-Needed (MAAN) scheme is proposed to encourage subjects to participate actively and avoid the slack of the subjects including two modules: Functional Capability Estimation (FCE) and Mirror Adaptation (MAD). Specifically, the first MSFE module can obtain joint functional capability based on fused biological and motional signals. The second MAD module acquires the needed assistance via the estimated torques of FCE based on healthy limb. Through the iteration and collaboration of these two modules, a human-in-the-loop adaptive training is achieved to promote the patient participation. The results demonstrate that the MAAN strategy can generate suitable assistance for the patients to correct abnormal muscle activation patterns and promote active voluntary participation. Compared with other methods, the proposed strategy improves motion stability and consistency with the natural physiological state of healthy limbs. This research can be expected to greatly enhance the rehabilitation and power assistance outcome of exoskeleton robot in more practical applications. © 2022 IEEE.

关键词： Mirrors

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Single-step precision programming of decoupled multiresponsive soft millirobots

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Proceedings of the National Academy of Sciences of the United states of America 2024年第13期121卷 e2320386121页

作者： Zheng, Zhiqiang Han, Jie Shi, Qing Demir, Sinan Ozgun Jiang, Weitao Sitti, Metin Physical Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart 70569 Germany State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Xi’an 710054 China School of Mechanical Engineering Xi’an Jiaotong University Xi’an 710054 China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology) Ministry of Education Beijing 100081 China Institute for Biomedical Engineering ETH Zurich Zurich 8092 Switzerland School of Medicine College of Engineering Koç University Istanbul 34450 Turkey

Stimuli-responsive soft robots offer new capabilities for the fields of medical and rehabilitation robotics, artificial intelligence, and soft electronics. Precisely programming the shape morphing and decoupling the multiresponsiveness of such robots is crucial to enable them with ample degrees of freedom and multifunctionality, while ensuring high fabrication accuracy. However, current designs featuring coupled multiresponsiveness or intricate assembly processes face limitations in executing complex transformations and suffer from a lack of precision. Therefore, we propose a one-stepped strategy to program multistep shape-morphing soft millirobots (MSSMs) in response to decoupled environmental stimuli. Our approach involves employing a multilayered elastomer and laser scanning technology to selectively process the structure of MSSMs, achieving a minimum machining precision of 30 µm. The resulting MSSMs are capable of imitating the shape morphing of plants and hand gestures and resemble kirigami, pop-up, and bistable structures. The decoupled multistimuli responsiveness of the MSSMs allows them to conduct shape morphing during locomotion, perform logic circuit control, and remotely repair circuits in response to humidity, temperature, and magnetic field. This strategy presents a paradigm for the effective design and fabrication of untethered soft miniature robots with physical intelligence, advancing the decoupled multiresponsive materials through modular tailoring of robotic body structures and properties to suit specific applications. Copyright © 2024 the Author(s).

关键词： environmental response miniature robot soft electronics soft robotics

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Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth Estimation

arXiv

引用

arXiv 2023年

作者： Hu, Junjie Fan, Chenyou Zhou, Liguang Gao, Qing Liu, Honghai Lam, Tin Lun The Chinese University of Hong Kong Shenzhen China The School of Artificial Intelligence South China Normal University China The School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China State Key Laboratory of Robotics and systems Harbin Institute of Technology Shenzhen China The School of Science and Engineering The Chinese University of Hong Kong Shenzhen China

With the rapid advancements in autonomous driving and robot navigation, there is a growing demand for lifelong learning models capable of estimating metric (absolute) depth. Lifelong learning approaches potentially offer significant cost savings in terms of model training, data storage, and collection. However, the quality of RGB images and depth maps is sensor-dependent, and depth maps in the real world exhibit domain-specific characteristics, leading to variations in depth ranges. These challenges limit existing methods to lifelong learning scenarios with small domain gaps and relative depth map estimation. To facilitate lifelong metric depth learning, we identify three crucial technical challenges that require attention: i) developing a model capable of addressing the depth scale variation through scale-aware depth learning, ii) devising an effective learning strategy to handle significant domain gaps, and iii) creating an automated solution for domain-aware depth inference in practical applications. Based on the aforementioned considerations, in this paper, we present i) a lightweight multi-head framework that effectively tackles the depth scale imbalance, ii) an uncertainty-aware lifelong learning solution that adeptly handles significant domain gaps, and iii) an online domain-specific predictor selection method for real-time inference. Through extensive numerical studies, we show that the proposed method can achieve good efficiency, stability, and plasticity, leading the benchmarks by 8% ∼ 15%. The code is available at https://***/Freeformrobotics/Lifelong-MonoDepth. © 2023, CC BY.

关键词： Numerical methods

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Evacuation Problem Under the Nuclear Leakage Accident

Evacuation Problem Under the Nuclear Leakage Accident

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第40届中国控制会议

作者： Canqi Yao Shibo Chen Zaiyue Yang School of Mechatronics Engineering Harbin Institute of Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineeringand the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in UniversitiesSouthern University of Science and Technology

To handle the detrimental effects brought by leakage of radioactive gases at nuclear power station, we propose a bus based evacuation optimization problem. The proposed model incorporates the following four constraints, 1) the maximum dose of radiation per evacuee, 2) the limitation of bus capacity, 3) the number of evacuees at demand node（bus pickup stop）,4) evacuees balance at demand and shelter nodes, which is formulated as a mixed integer nonlinear programming（MINLP）problem. Then, to eliminate the difficulties of choosing a proper M value in Big-M method, a Big-M free method is employed to linearize the nonlinear terms of the MINLP problem. Finally, the resultant mixed integer linear program（MILP） problem is solvable with efficient commercial solvers such as CPLEX or Gurobi, which guarantees the optimal evacuation plan *** evaluate the effectiveness of proposed evacuation model, we test our model on two different scenarios（a random one and a practical scenario）. For both scenarios, our model attains executable evacuation plan within given 3600 seconds computation time.

关键词： Nuclear leakage accident bus evacuation problem mixed integer nonlinear programming

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