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检索条件"机构=Henan Provincial Key Laboratory of Robotics and Intelligent Systems"

共 257 条记录，以下是81-90 订阅

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Leg Transmission Mechanism for Enhanced Load-Carrying Capacity: Knee Joint Torque Optimization Design

Leg Transmission Mechanism for Enhanced Load-Carrying Capaci...

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IEEE International Conference on Development and Learning, ICDL

作者： Quan Huang Yixuan Guo Haoyun Yan Yuquan Leng Shoubin Liu Chenglong Fu School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

This study proposes an optimized design for the leg transmission structure of a quadruped robot, aiming to enhance the load-bearing capacity of the knee joint. Firstly, the dynamic simulation of the single leg's load-lifting process in the quadruped robot is conducted, indicating higher torque demands on the knee joint during this process. Therefore, a leg transmission mechanism, combining a ball screw mechanism and a crank-slider mechanism, is designed to effectively amplify the torque of the knee joint motor. Subsequently, a virtual prototype of the quadruped robot, incorporating this design, is constructed using Adams software. The foot trajectory of the robot is pre-planned, and the joint trajectories are obtained through inverse kinematics, using them as the driving functions for the quadruped robot to perform actions such as load lifting, static standing, and diagonal walking gait. Finally, the knee joint torque and corresponding motor driving torque of the quadruped robot's legs are measured and compared. The results demonstrate that the driving torque of the knee joint motor is effectively amplified by the leg transmission mechanism, with the maximum amplification observed during the initial stage of load lifting, reaching a magnification factor of nearly 7.66 times. This verifies the effectiveness of the proposed leg transmission mechanism in enhancing the load-bearing capacity of the knee joint.

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A History Information-Based A* Algorithm for the Path Planning with Multiple Alternative Destinations

A History Information-Based A* Algorithm for the Path Planni...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Ke Wang Wei Liang Huaguang Shi Jialin Zhang Qi Wang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Artificial Intelligence Henan University Zhengzhou China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

As a cornerstone technology in automation, path planning plays a crucial role across various domains, including logistics, autonomous vehicles, and robotics. A novel path planning challenge, focusing on routes with multiple alternative destinations, has emerged as a focal point in industrial settings. Traditional approaches such as breadth-first and heuristic searches lack specific optimizations for this challenge, resulting in suboptimal efficiency. This paper introduces a new approach to the path planning problem with multiple alternative destinations that utilizes historical data. It features three heuristic strategies: leveraging historical information for search acceleration, pruning based on the length of the current shortest path, and searching in ascending order of the Manhattan distance. These strategies enhance the search efficiency by leveraging historical information for faster searches and pruning based on real-time search outcomes. Simulation results show that the proposed algorithm outperforms the existing works in terms of the computational cost.

关键词： Service robots Navigation Simulation Focusing Path planning Real-time systems Computational efficiency

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Real-time Terrain Recognition based on Transformer and Gait Prediction based on CNN-LSTM-Attention for Exosuit

Real-time Terrain Recognition based on Transformer and Gait ...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Yang, Fangliang Chen, Chunjie Wang, Zhuo Xu, Yinsheng Liu, Yao Wu, Xinyu University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Guilin University of Technology Guilin541004 China

ISBN: (纸本)9798350327182

For wearable soft exosuits, an imprecise control strategy can easily injure the wearer, while real-time terrain recognition and accurate gait phase estimation can effectively improve the control strategy of the exosuit and make the wearer comfortable and safe. In this paper, a real-time terrain recognition algorithm based on Transformer and a gait estimation algorithm based on CNN-LSTM-Attention are implemented. The Transformer-based recognition of different terrains improves the recognition accuracy to some extent, and the CNN-LSTM-Attention based feature extraction for temporal signals such as gait phase is also extremely noticeable. Experiments show that the Transformer-based algorithm achieves 99.64 % recognition accuracy in six different terrain environments. In the gait phase estimation experiment, CNN-LSTM-CBAM achieved the best performance with an evaluation index r2 of 0.9221. The aforementioned terrain recognition algorithms and gait phase estimation algorithms may have a positive impact on soft exosuit and dynamic prosthetics research. © 2023 IEEE.

关键词： Landforms

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A Stair-Climbing Robot with Star-wheel Configuration

A Stair-Climbing Robot with Star-wheel Configuration

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IEEE International Conference on robotics and Biomimetics

作者： Tongxin Cui Wenhui Wang Zheng Zhu Jing Wu Zhenzhong Jia Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology (SUSTech) Shenzhen China

ISBN: (纸本)9781665481106

This paper proposes a four-wheel mobile robot that uses passive star-wheel configuration to climb stairs. Without adding any control complexity, the robot can climb a standard indoor staircase of 15 x 28cm at a speed of 0.7 $s$ / step. For stairs of other sizes, it also has a certain adaptability, avoiding the problem of slipping when using active star-wheel to climb stairs. This paper analyzes the obstacle-surmounting conditions of the four-star-wheel robot during stair climbing, and uses statics to calculate the driving torque. We use simulation to validate the torque consumption study, and prove the stability of the robot's central trajectory during stair climbing. These results provide a basis to quantify the robot's stair-climbing capability under certain load. We build an robot prototype platform and conduct physical experimentation to validate the robot performance.

关键词： Torque Prototypes Stairs Stability analysis Trajectory Complexity theory Mobile robots

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Shape Optimization of Magnetorheological Brake for Performance Enhancement

Shape Optimization of Magnetorheological Brake for Performan...

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IEEE International Conference on robotics and Biomimetics

作者： Qiuyu Shi Fajiang Liu Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Magnetorheological (MR) rotary brakes leverage the magnetically controllable rheological properties of MR fluids to provide damping torque in lower limb assistance devices. This paper utilizes an optimization algorithm (Whale Optimization Algorithm (WOA)) to optimize the geometric dimension of the MR brake to enhance field-dependent brake torque. First, the mechanical design and optimization process of the MR brake were outlined. Then, the magnetic density of the MR fluid is evaluated using the ANSYS platform. With that, the WOA was exploited to optimize key design parameters across multiple iterations. According to the simulated results, the torque was improved from 17.39 Nm to 25.89 Nm, which increased by 48%. Finally, a prototype with the initial dimension was fabricated and preliminarily tested.

关键词： Stator cores Torque Fluids Shape Magnetomechanical effects Prototypes Magnetic liquids Whale optimization algorithms Brakes Optimization

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A Track-based Colon Endoscopic Robot with Depth Perception Stereo Cameras for Haustral Fold Detection during Colonic Navigation

A Track-based Colon Endoscopic Robot with Depth Perception S...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shujing He Yujie Zhang Baoyi Huang Jie Lin Chaoyang Shi Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Guangzhou University of Chinese Medicine Shenzhen China Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education School of Mechanical Engineering Tianjin University Tianjin China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Colon endoscopic robots represent a promising screening modality for the visualization of colon cancers with high sensitivity. However, current colonoscopy robots are often characterized by intricate and bulky mechanical structures, which pose practical challenges when moving through the complex and narrow environment of the colon. Moreover, these robots are typically equipped with a single camera, limiting their ability to accurately estimate the depth of haustral folds in the colon, which is of great importance for the active colonic navigation of the robots. To address these challenges, we develop a track-based stereoscopic endoscopic robot (TSER) which is equipped with four tracks positioned at the corners of its body. This innovative design maximizes the contact between the tracks and the colon wall, enhancing maneuverability. The tracks are constructed from de-molded polydimethylsiloxane (PDMS) and incorporate micro-patterns on their outer surfaces. We have proposed a straightforward strategy for detecting haustral folds using TSER’s stereo camera, which allows for precise identification of their position and depth. The TSER achieves an average motion speed of 9.8 mm/s in a bellows tube that contains silicone oil and a speed of 5.2 mm/s in an exvivo porcine intestinal segment. Impressively, the TSER boasts an 88.11% accuracy rate in haustral fold depth estimation, surpassing the performance of existing geometric shape fitting methods. These results demonstrate that the TSER holds great potential for effective and efficient movement and inspection within the colon, offering a promising solution for improved colon cancer screening.

关键词： Visualization Sensitivity Tracking Navigation Shape Stereo image processing Oils

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Flexible Multi-Channel Electrical Stimulation System for Assisting Grasping in Patients with Hemiplegia

Flexible Multi-Channel Electrical Stimulation System for Ass...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Jinxin Sun Guojing Huang Chengyu Lin Wei Pan Kong Hoi Cheng Guotao Gou Shuyan Huang Yuquan Leng Chenglong Fu Zhencheng Chen Guangxi Human Physiological Information Non Invasive Detection Engineering Technology Research Center School of Life and Environmental Sciences Guilin University of Electronic Technology Guilin China Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Stroke patients are unable to perform gripping actions effectively as normal individuals due to impaired hand function. Electrical stimulation is currently a relatively effective rehabilitation method, but there is still room for improvement in aspects such as grip control precision and grip posture selection. Therefore, we propose a multi-channel electrical stimulation system to achieve precise control of hand gripping in stroke patients and assist in hand function rehabilitation. The pressure-controlled constant current source electrical stimulation system is proposed and a flexible wearable 16-channel hand FPC electrical stimulation patch is designed according to the distribution of hand muscles. The MCU controls an external DAC chip to generate voltage to drive the pressure-controlled constant current source, thereby generating adjustable biphasic symmetrical stimulation pulse waveforms. The FPC transmits the generated stimulation pulses to the corresponding stimulation points to achieve precise electrical stimulation of specific points. Through three comparative experiments, the results indicate that precise control of finger movement angles has been achieved by adjusting the stimulation current and frequency. The flexible multi-channel hand electrical stimulation system offers a solution for restoring motor function in patients with hemiplegia.

关键词： Mechatronics Thumb Electrical stimulation Bending Stroke (medical condition) Muscles Motors Voltage control Frequency control Robots

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IMU-Based Prediction of Multiple Grasping Gesture Intentions for Enhanced Functional Electrical Stimulation Control*

IMU-Based Prediction of Multiple Grasping Gesture Intentions...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Guotao Gou Kong Hoi Cheng Jinxin Sun Chengyu Lin Wei Pan Guojing Huang Yuquan Leng Yixuan Guo Chenglong Fu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Guangxi Human Physiological Information Non Invasive Detection Engineering Technology Research Center School of Life and Environmental Sciences Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Stroke survivors frequently face the challenge of regaining hand-grasping functions, which are crucial for performing daily activities. While Functional Electrical Stimulation (FES) has demonstrated promise for hand function recovery, the application of online control methods tailored to varied daily grasps remains underexplored. In response, our study presents a refined framework utilizing an inertial measurement unit (IMU) for the real-time recognition of grasp intentions in stroke patients. Data on arm trajectories and orientations preceding diverse grasping actions were gathered from three healthy individuals, segmented by acceleration to determine high-accuracy intervals for grasp prediction. The Support Vector Classification (SVC) model emerged as a superior method for intent recognition. By segmenting data based on acceleration, our model’s general accuracy improved. Moreover, the time required to achieve a stable accuracy rate exceeding 95% was reduced from 0.8 s to 0.2 s. This research lays the groundwork for future advancements in online gesture recognition systems. The successful implementation of FES based on SVC-model predictions mark a significant step toward intuitive and adaptive rehabilitation therapies for stroke patients.

关键词： Accuracy Static VAr compensators Grasping Stroke (medical condition) Real-time systems Iron Data models Trajectory Neuromuscular stimulation Context modeling

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A new structure of end-effector traction upper limb rehabilitation robot

A new structure of end-effector traction upper limb rehabili...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Li, Liaoyuan Han, Jianhai Li, Xiangpan Guo, Bingjing Xia, Pengpeng Du, Ganqin Henan University of Science and Technology Key Laboratory of Robotics and Intelligent Systems School of Mechanical and Electrical Engineering Luoyang471000 China First Affiliated Hospital of Henan University of Science and Technology Department of Neurology Luoyang471000 China

ISBN: (纸本)9781665436786

Among the rehabilitation therapies for patients with stroke or paralysis, robot-assisted rehabilitation is a research hotspot now. However, there are not many cases of clinical application, mainly because of the complex structure, single function, or high cost. This research proposes a new type of 3-DOF (degrees of freedom) upper limb rehabilitation robot in series structure of with an end-effector, which has 2 degrees of freedom in horizontal rotation and 1 degree of freedom in the vertical movement. It has a compact structure, saves space, is easy to be moved and can realize rehabilitation training in three-dimensional space. It is mainly used for rehabilitation training of the shoulder and elbow joints of the upper limbs. The first two rotary joints are driven by AC servo motors, and the prismatic joint is driven by a single-acting cylinder, which increases the passive compliance of the robot. In addition, a three-dimensional force sensor is added to expand the human-machine interaction channel and increase the active safety of the robot. Through the trajectory tracking and force control test of the robot, it is proved that the device can meet the demand of passive and active upper limb rehabilitation. © 2021 IEEE.

关键词： End effectors

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Cam Profile Optimization for a Piezoelectric-Based Sole Energy Harvester

Cam Profile Optimization for a Piezoelectric-Based Sole Ener...

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IEEE International Conference on robotics and Biomimetics

作者： Haisu Liao Zhongliang Ren Yidi Wang Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Harvesting energy from the human body to extend the operational time for low-power has gained significant attention. Recently, researchers have focused on biomechanical energy harvesting from human feet while walking. This paper presents an optimization of the cam profile for a piezoelectric-based sole energy harvester designed to be worn on the bottom of shoes to power electronic devices. Specifically, cams with linear polynomial and exponential functions were designed to actuate the piezoelectric transducers (PZTs). Force analysis revealed that the exponential function cam induces more significant deformation in the PZTs than the linear polynomial cam. Preliminary tests on a healthy subject validated this design, showing that the exponential function cam produced an average output power of 0.16mW at a walking speed of 5.5 km/h, indicating a 78% improvement over the linear polynomial cam. Moreover, the optimization rate increased with the growing walking speed.

关键词： Legged locomotion Deformation Force Voltage Polynomials Energy harvesting Power generation Optimization Lead zirconate titanate Testing

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