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Positioning system design of closed-loop magnetically driven laser steering manipulator for endoscopic microsurgery

Biomimetic intelligence & robotics 2023年第4期3卷 40-46页

作者： Qi Zhang Han Xu Li Zhu Li Liu School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin 541004China Shenzhen Key Laboratory of Robotic Perception and Intelligence Department of Electronic and Electrical EngineeringSouthern University of Science and TechnologyShenzhen 518055China

This study presents a closed-loop magnetically driven laser steering manipulator positioning system for endoscopic microsurgery.A multimagnetic field strength sensor circuit is embedded in a 16−mm diameter analog laser steering *** magnetic field distribution of a cylindrical permanent magnet in three-dimensional space is first modeled using an integral model to overcome the large error induced by the magnetic dipole model when the sensor and permanent magnet are *** integral in the model is then decomposed using the Gauss–Legendre quadrature to improve the computational efficiency of the ***,five commonly used global search optimization methods are ***,the algorithm with the fastest computational rate among these five algorithms,the tree-seed algorithm,is fused with the Levenberg–Marquardt algorithm,which performs well in local search,to obtain a hybrid optimization ***,it is demonstrated through static and dynamic experiments that the system based on the hybrid algorithm can obtain satisfactory computational errors while maintaining a high computational rate.

关键词： Magnetic localization Minimally invasive surgery Hybrid optimization algorithm Robot-assisted surgery

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DS-Seq: Deriving Smooth 3D Human Motion Sequences from Video Time Cues 41st

DS-Seq: Deriving Smooth 3D Human Motion Sequences from Vide...

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41st Computer Graphics International Conference, CGI 2024

作者： Peng, Tao Peng, Delang Li, Li Liu, Junping Zhang, Zili Hu, Xinrong School of Computer and Artificial Intelligence Wuhan Textile University Wuhan China China NationalTextile and ApparelCouncil Key Laboratory of Intelligent Perception and Computing Shenzhen China

ISBN: (纸本)9783031818059

When applying the methods for reconstructing the 3D poses and shapes of human bodies based on single-frame images to videos, the insufficient reconstruction accuracy of individual frames and the unbalanced utilization of information from the current frame, past frames, and future frames often lead to the inability to restore high-precision and smooth 3D human motion. Specifically, this results in irregular jitter in the generated human motion. To address this issue, we propose a mesh recovery system (DS-Seq). By utilizing a higher-precision 2D feature detection framework and leveraging a motion constraint framework based on temporal features to equally incorporate information from past and future frames, our DS-Seq can reconstruct smooth 3D human motion. Additionally, the precision of 3D poses and shapes per frame achieved by our DS-Seq surpasses that of the current state-of-the-art method TCMR by over 10%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 3D modeling

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Collaborative Fall Detection and Response Using Wi-Fi Sensing and Mobile Companion Robot

Collaborative Fall Detection and Response Using Wi-Fi Sensin...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chen, Yunwang Kang, Yaozhong Zhao, Ziqi Hong, Yue Meng, Lingxiao Meng, Max Q.-H. Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen518055 China SUSTech Department of Electrical and Electronic Engineering Shenzhen China School of System Design and Intelligent Manufacturing SUSTech Shenzhen China

ISBN: (纸本)9781665481090

This paper presents a collaborative fall detection and response system integrating Wi-Fi sensing with robotic assistance. The proposed system leverages channel state information (CSI) disruptions caused by movements to detect falls in non-line-of-sight (NLOS) scenarios, offering non-intrusive monitoring. Besides, a companion robot is utilized to provide assistance capabilities to navigate and respond to incidents autonomously, improving efficiency in providing assistance in various environments. The experimental results demonstrate the effectiveness of the proposed system in detecting falls and responding effectively. © 2024 IEEE.

关键词： Fall detection

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SkyvoltRobot: A Novel Rail-Mounted Charging Robot for Electric Vehicles

SkyvoltRobot: A Novel Rail-Mounted Charging Robot for Electr...

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

作者： Hu, Anjun Ban, Shu Hong, Yue Zhao, Ziqi Zhao, Fucheng Wang, Jiankun Meng, Max Q.-H. Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China

SkyvoltRobot represents an innovative solution for electric vehicle (EV) charging services. This system achieves higher efficiency and broader coverage by transporting charging units with robots suspended on overhead tracks. The solution relies on the robots' ability to grasp and transport charging units, utilizing a specially designed two-stage telescopic mechanism to complete the task accurately. Compared to existing fixed-point charging solutions, this system covers a much larger area with the same number of charging units. It significantly reduces economic costs for the same coverage area. A single robot can manage multiple charging units' transportation, allowing for future multi-area track transfers. Notably, we have innovatively designed a SkyVoltRobot and experimentally demonstrated the effectiveness of this solution. © 2024 The Authors.

关键词： Microrobots

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CAAI Transactions on intelligence Technology 2022年第1期7卷 26-33页

作者： Hong Liu Peipei Yuan Bing Yang Ge Yang Yang Chen Key Laboratory of Machine Perception Shenzhen Graduate SchoolPeking UniversityShenzhenChina School of Artificial Intelligence Chongqing University of TechnologyChongqingChina Yanka Kupala State University of Grodno GrodnoBelarus

Various time-frequency(T-F)masks are being applied to sound source localization ***,deep learning has dramatically advanced T-F mask ***,existing masks are usually designed for speech separation tasks and are suitable only for single-channel signals.A novel complex-valued T-F mask is proposed that reserves the head-related transfer function(HRTF),customized for binaural sound source *** addition,because the convolutional neural network that is exploited to estimate the proposed mask takes binaural spectral information as the input and output,accurate binaural cues can be *** with conventional T-F masks that emphasize single speech source–dominated T-F units,HRTFreserved masks eliminate the speech component while keeping the direct propagation ***,the estimated HRTF is capable of extracting more reliable localization features for the final direction of arrival ***,binaural sound source localization guided by the proposed T-F mask is robust under noisy and reverberant acoustic *** experimental results demonstrate that the new T-F mask is superior to conventional T-F masks and lead to the better performance of sound source localization in adverse environments.

关键词： estimation. sound function

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Graph neural network based method for robot path planning

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Biomimetic intelligence & robotics 2024年第1期4卷 80-87页

作者： Xingrong Diao Wenzheng Chi Jiankun Wang Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical EngineeringSouthern University of Science and TechnologyShenzhen 518055China Robotics and Microsystems Center School of Mechanical and Electric EngineeringSoochow UniversitySuzhou 215021China Jiaxing Research Institute Southern University of Science and TechnologyJiaxing 314000China

Sampling-based path planning is widely used in robotics,particularly in high-dimensional state *** the path planning process,collision detection is the most time-consuming ***,we propose a learning-based path planning method that reduces the number of collision *** develop an efficient neural network model based on graph neural *** model outputs weights for each neighbor based on the obstacle,searched path,and random geometric graph,which are used to guide the planner in avoiding *** evaluate the efficiency of the proposed path planning method through simulated random worlds and real-world *** results demonstrate that the proposed method significantly reduces the number of collision checks and improves the path planning speed in high-dimensional environments.

关键词： Graph Neural Network(GNN) Collision detection Sampling-based path planning

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A Novel Serial-Parallel Hybrid Robot for Rehabilitation Training of Gait and Balance 9

A Novel Serial-Parallel Hybrid Robot for Rehabilitation Trai...

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9th International Conference on Electrical Engineering, Control and robotics, EECR 2023

作者： Shi, Mingsong Hao, Liziyi Zhou, Zhaocheng Liu, Sihui Han, Jianda Yu, Ningbo Nankai University Tianjin Key Laboratory of Intelligent Robotics College of Artificial Intelligence Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Guangdong Shenzhen518083 China

ISBN: (纸本)9781665491204

Robot-assisted rehabilitation training for lowerlimb function recovery has gained increasing acceptability, but simultaneous training of gait and balance has not been well explored. In this paper, we propose a novel 5-DOF serial-parallel hybrid end-effort robot to provide gait training, balance training, as well as gait and balance training. Each side of the robot is composed of a 2-DOF gait generator and a 3-DOF parallel balance module. The gait generator takes the H-Bot mechanism, which distributes the heavy load of the patient to the two motors during walking, which are connected in serial. For the balance module, its virtual rotation center of the footplate is designed to be aligned with the ankle joint, enabling natural balance adjustment and training. Further, two displacement sensors and an inclinometer are employed to measure the pose, and closed-loop control of the 2-DOF position and 3-DOF orientation of the robot end-effector is realized. The robotic system has been built up, and achieved good performance on position and pose tracking, promising an effective rehabilitation platform for independent and simultaneous training of gait and balance. © 2023 IEEE.

关键词： End effectors

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Disturbance Observer-Based Robust Control for Redundant Manipulators Towards Conditional Monitoring

Disturbance Observer-Based Robust Control for Redundant Mani...

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

作者： Ma, Tie-Nan Xi, Rui-Dong Liang, Wei-Xiang Yang, Zhi-Xin Department of Electromechanical Engineering Faculty of Science and Technology University of Macau Taipa999078 China Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China

Conditional monitoring is crucial for preserving the functionality and longevity of electro-mechanical equipment. The adoption of robots is an effective method for improving the traditional approaches that rely on fixed monitoring sites. Therefore, this work investigates the motion control of a redundant robot manipulator in operational space for the application of conditional monitoring. A simple and efficient kinematic tracking differentiator (KTD) is proposed to convert operational space trajectories into joint space tracking. Redundancy is handled using a null space vector with time delay method. Additionally, a fixed-time terminal sliding mode controller (FxTSMC) is designed with a disturbance observer to improve fast convergence and disturbance rejection ability. Simulation results have been demonstrated to show the effectiveness of the proposed control scheme. © 2024 The Authors.

关键词： Disturbance rejection

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Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications 38

Robust and Faster Zeroth-Order Minimax Optimization: Complex...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： An, Weixin Liu, Yuanyuan Shang, Fanhua Liu, Hongying Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education School of Artificial Intelligence Xidian University China College of Intelligence and Computing Tianjin University China Medical School Tianjin University China Peng Cheng Lab Shenzhen China

Many zeroth-order (ZO) optimization algorithms have been developed to solve nonconvex minimax problems in machine learning and computer vision areas. However, existing ZO minimax algorithms have high complexity and rely on some strict restrictive conditions for ZO estimations. To address these issues, we design a new unified ZO gradient descent extragradient ascent (ZO-GDEGA) algorithm, which reduces the overall complexity to O(dϵ-6) to find an ϵ-stationary point of the function ψ for nonconvex-concave (NC-C) problems, where d is the variable dimension. To the best of our knowledge, ZO-GDEGA is the first ZO algorithm with complexity guarantees to solve stochastic NC-C problems. Moreover, ZO-GDEGA requires weaker conditions on the ZO estimations and achieves more robust theoretical results. As a by-product, ZO-GDEGA has advantages on the condition number for the NC-strongly concave case. Experimentally, ZO-GDEGA can generate more effective poisoning attack data with an average accuracy reduction of 5%. The improved AUC performance also verifies the robustness of gradient estimations. © 2024 Neural information processing systems foundation. All rights reserved.

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Ethical Decision-making for Autonomous Driving based on LSTM Trajectory Prediction Network

Ethical Decision-making for Autonomous Driving based on LSTM...

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2023 International Conference on Biomimetic intelligence and robotics

作者： Wei, Wen Wang, Jiankun Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China

The development of autonomous vehicles has brought a great impact and changes to the transportation industry, offering numerous benefits i n t erms o f s afety a nd e fficiency. How ever, one of the key cha llenges tha t aut onomous dri ving fac es is how to make ethical decisions in complex situations. To address this issue, in this article, a novel trajectory prediction method is proposed to achieve ethical decision-making for autonomous driving. Ethical considerations are integrated into the decision-making process of autonomous vehicles by quantifying the utility principle and incorporating them into mathematical formulas. Furthermore, trajectory prediction is optimized using LSTM network with an attention module, resulting in improved accuracy and reliability in trajectory planning and selection. Through extensive simulation experiments, we demonstrate the effectiveness of the proposed method in making ethical decisions and selecting optimal trajectories. © 2023 The Authors. Published by Elsevier B.V.

关键词： Decision making

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