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检索条件"任意字段=5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023"

共 62 条记录，以下是51-60 订阅

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A Disturbance Compensation Method Using Adaptive Neural Network for robotic Manipulator 5

A Disturbance Compensation Method Using Adaptive Neural Netw...

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5th world robot conference symposium on advanced robotics and automation, wrc sara 2023

作者： Yang, Siqin Lu, Chunheng Luo, Xuejin Wang, Junchen Beihang University School of Mechanical Engineering and Automation Beijing100191 China

ISBN: (纸本)9798350307320

In contact with the hardest human tissues, such as bones and teeth, performing force control precisely is the key for improving operation effect and ensuring surgical safety. this article introduces an intuitive six degree-of-freedoms (6-DoF) task space PD control to track a given trajectory based on a linear and decoupled model for six dimensional pose (rotational and positional) displacement. then, an adaptive neural network (NN) controller is designed to deal with the nonlinearities of the system. A learning method based on the radial basis function NN (RBFNN) is involved in controller design to compensate for the manipulator's dynamic uncertainties. the stability of the controller is proved by using Lyapunov stability principles. Finally, the effectiveness of the proposed methods are validated through a group of setpoint control and trajectory tracking control simulations on a redundant robotic manipulator. the mean error of setpoint control with robotic uncertainties after compensation was 4. 47×10{-9}m, 1.42×10{-8}m, -1.22×10{-7}m, in axis X, Y, Z respectively. the maximum error of trajectory tracking in task space was less than 1 mm. © 2023 IEEE.

关键词： Controllers

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Event-Potential Method for Mobile robot Motion Planning and Control 5

Event-Potential Method for Mobile Robot Motion Planning and ...

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5th world robot conference symposium on advanced robotics and automation, wrc sara 2023

作者： Sheng, Yongji Ye, Jiajie Wang, Siyu Liu, Xinyu Xi, Ning The University of Hong Kong Department of Industrial and Manufacturing Systems Engineering Pokfulam Hong Kong

ISBN: (纸本)9798350307320

Motion planning and control of mobile robots is a challenging but crucial task for autonomous navigation. Since the actual environment is usually highly dynamic and has extremely high uncertainty and unpredictability, motion planning and control methods need to handle unexpected events and uncertainties in the environment, such as dynamic obstacles. Existing motion planning and control methods are usually decoupled processes. When unexpected events occur, the planner replans a new feasible plan based on new sensory information, and then the controller executes the new plan. Existing methods usually perform the perception, replanning, and control loop in real time. Replanning is an inefficient and time-consuming process since the robot needs to process new perception information and restart the planner. Also, the plan is not fully executed before the next loop which wastes most of the plan. We tackle this problem by introducing an event-potential method: a novel event-based potential field motion planning and control method that introduces event reference instead of time reference, which can locally modify the preplanned velocity along the trajectory using the resultant force generated by the attractive force from a trajectory and repulsive force from obstacles for obstacle avoidance. After completing obstacle avoidance, the event reference allows the robot to continue to track the original trajectory without replanning. We test and compare the eventpotential method with existing methods on a three-wheeled omnidirectional mobile robot. the framework can also be adapted to different robots and tasks. © 2023 IEEE.

关键词： Trajectories

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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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Edge Detection and Alignment Control Method for Mobile robots based on multi-Lidar Fusion 5

Edge Detection and Alignment Control Method for Mobile Robot...

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5th world robot conference symposium on advanced robotics and automation, wrc sara 2023

作者： Gao, He Tao, Yong Liu, Xiaonan Zhang, Yufan Liu, Haitao Wan, Jiahao Beihang University Research Institute of Aero-Engine Beijing102206 China Beijing New Materials and New Energy Technology Development Promotion Center Administrative Commission of Zhongguancun Science Park Beijing100191 China Beihang University School of Large Aircraft Engineering Beijing100191 China Beihang University School of Mechanical Engineering and Automation Beijing100191 China

ISBN: (纸本)9798350307320

Currently, there is a growing demand for intelligent maintenance of large-scale infrastructure, prompting a shift from manual to semi-automatic solutions in the control schemes of inspection robots. Mobile inspection robots play a crucial role in tasks such as flip-over inspection, fall prevention warning, defect identification, all of which necessitate edge detection and alignment processes. Laser alignment, with its high precision and low computational complexity, offers significant advantages over manual observation and visual alignment methods. this paper addresses practical engineering requirements by proposing a lidar-based structural edge detection algorithm and an automatic alignment controller. To validate the effectiveness of the proposed method, edge detection and alignment control experiments were conducted in a simulated environment. the results show that the edge detection algorithm reduces the direction detection error to 2.7°. the developed alignment controller exhibits a convergence time approximately 40% shorter than the standard PID controller. the proposed scheme effectively meets the accuracy and real-time requirements for edge detection and automatic alignment functions in mobile inspection robots and holds significant application potential for the infrastructure project's intelligent maintenance. © 2023 IEEE.

关键词： Alignment

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Hair Direction Detection 6

Hair Direction Detection

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6th world robot conference (wrc) / symposium on advanced robotics and automation (sara)

作者： Bal, Peng Wang, Pengyi Wu, Hongde Yang, Qian Feng, Yongqiang Wang, Junchen Hu, Yida David Li, Changsheng Liu, Wenyong Kuang, Shaolong Su, Bai-Quan Beijing Univ Posts & Telecommun Sch Intelligent Engn & Automat Med Robot Lab Beijing 100876 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Plast Surg Hosp Beijing 100041 Peoples R China Beihang Univ Sch Mech Engn & Automat Beijing 100083 Peoples R China Harvard Med Sch Brigham & Womens Hosp Boston MA 02115 USA Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Beijing 100081 Peoples R China Beihang Univ Beijing Adv Innovat Ctr Biomed Engn Sch Biol Sci & Med Engn Key Lab Biomech & MechanobiolChinese Educ Minist Beijing 100083 Peoples R China Shenzhen Univ Technol Sch Hlth Sci & Environm Engn Shenzhen 518060 Peoples R China

ISBN: (纸本)9798331506100

Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for the problem of recognising hair direction. the main goal of this paper is to develop an algorithm that can identify hair direction in a complex image environment. A curve segment analysis method based on image skeletonisation is adopted, which is based on skeleton extraction, intersection identification, curve segmentation and direction prediction. In addition, this paper combines the technique of non-maximal value suppression and PCA analysis to improve the accuracy and stability of the estimation. In the experimental design, this paper chooses a representative image dataset to verify the effectiveness of this paper's algorithm. the experimental process includes the steps of image preprocessing, skeletonisation processing, intersection detection and merging, and direction prediction. the experimental results show that the method in this paper can accurately and effectively identify the hair direction. the main contribution of this paper is to propose a new hair direction recognition method and experimentally verify its effectiveness and accuracy in complex backgrounds.

关键词： Musculoskeletal system

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Structure Design and Dimension Optimization of FBG Enhanced Sensitization Equipment for Measuring Axial Tactile Micro-Force of Macular Hole Ophthalmic Surgical robot 4

Structure Design and Dimension Optimization of FBG Enhanced ...

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4th world robot conference (wrc) / symposium on advanced robotics and automation (sara)

作者： Li, Mingyang Zhang, Xiaodong Wang, Ning Zhang, Hongbing Feng, Xiaojing Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China 1 Xian Hosp Xian 710002 Peoples R China

ISBN: (数字)9781665463690

ISBN: (纸本)9781665463690

In macular hole surgery, the removal of the inner limiting membrane (ILM) is an effective method for the treatment of macular hole disease. However, due to the physical limits of the human body and the fragility of the patients' eyes, doctors cannot perceive the axial tactile micro-force between the tip of the surgical instrument and the patient's fundus, so it is likely to cause damage to the patients' eyes. therefore, accurately perceiving the intraoperative tactile micro-force can assist doctors to improve the operation accuracy. Based on the 5-DOF macular hole ophthalmic surgical robot established, structure design and dimension optimization of FBG enhanced sensitization equipment for measuring its axial insertion tactile micro-force are proposed in this paper, respectively. Firstly, by analyzing the surgical mechanism of macular hole, the operation is divided into two phases, the axial micro-force characteristics at the eyeball insertion phase are obtained, and it is impossible for FBG sensors to directly measure the axial micro-force. Secondly, by analyzing the force-sensitive areas where axial micro-force act on surgical instruments, the overall structure design of the axial tactile micro-force FBG enhanced sensitization equipment is completed. Finally, its sensitivity is further optimized by dimension optimization, and the axial tactile micro-force FBG sensing using enhanced sensitization equipment is verified by simulation.

关键词： Surgical robot FBG sensor Enhanced Sensitization Equipment Tactile Macular Hole Simulation

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Gait Planning and Motion Control Based on Vrep Simulation for Quadruped robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

引用

5th world robot conference symposium on advanced robotics and automation, wrc sara 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： robot programming

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4th world robot conference (wrc) / symposium on advanced robotics and automation (sara)

作者： Zhang, Xiaowen Yuan, Shuai Luan, Fangjun Lv, Jiaqi Liu, Guifu Shenyang Jianzhu Univ Sch Elect & Control Engn Shenyang 110168 Peoples R China Shenyang Jianzhu Univ Sch Comp Sci & Engn Shenyang 110168 Peoples R China

ISBN: (数字)9781665463690

ISBN: (纸本)9781665463690

Ship detection has always been an important and challenging task. Small ship targets and complex backgrounds in optical remote sensing images can both lead to false alarms and missed alarms in detection. the YOLO series algorithms have been widely used in optical remote sensing ship target detection, which has the advantage of fast detection speed. However, the YOLO series algorithms have poor detection performance when facing small targets. therefore, we propose a new algorithm, SMMA-YOLOv5, which can improve the model detection accuracy without significantly increasing the model size. We first introduce a self-attention mechanism to replace some of the convolutional layers to capture the global information of the feature map. Second, we integrate an efficient channel attention (ECA) model to the self-attention mechanism to enable information interaction between channels without adding additional computational overhead. Furthermore, we propose a new similarity mask structure to filter out the invalid regions in the feature map based on the elements' similarity. the experiments on the public MASATI ship dataset indicate that SMMA-YOLOv5 improves Precision by 3.9%, Recall by 5.3%, and AP by 5.4%, and prove the effectiveness of the algorithm while maintaining real-time detection.

关键词： Optical filters Computational modeling Object detection Filtering algorithms Optical imaging Information filters Real-time systems

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robotic Positioning in Percutaneous Transforaminal Endoscopic Discectomy Based on X-ray Image and DLT Algorithm 5

Robotic Positioning in Percutaneous Transforaminal Endoscopi...

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5th world robot conference symposium on advanced robotics and automation, wrc sara 2023

作者： Zhang, Tianyang Ji, Xuquan Zhu, Yuanyuan Zhang, Jian Geng, Baoduo Xue, Yumei Hu, Lei Liu, Wenyong Beihang University School of Mechanical Engineering and Automation Beijing100083 China Beihang University Key Laboratory of Biomechanics and Mechanobiology of the Ministry of Education Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical Engineering Beijing100083 China Beihang University School of Mathematics and Systems Science Beijing100083 China

ISBN: (纸本)9798350307320

Percutaneous transforaminal endoscopic discectomy (PTED) is a decompression surgery on patients with lumbar disc herniation and spinal canal stenosis in a minimally invasive environment, which greatly shorten the rehabilitation cycle of patients. However, the puncture of traditional PTED is performed under non-direct vision, which relies on the surgeon's clinical experience heavily and can easily cause collateral damage. In this paper, we propose a robotic positioning method in PTED based on X-ray image and DLT algorithm. the end-effector with three rings (EETR) for PTED positioning has been specially designed. During the operation, the 3D-2D transformation matrix is calculated by direct linear transform (DLT) algorithm. Finally, the motion parameters are calculated to control the robot. Based on our method, only one X-ray image is needed to complete the positioning, which also works well in a large range of deflection angle between EETR and target puncture channel. thus, it greatly simplifies the surgical process and reduces the radiation exposure time. By conducting a series of comparative experiments on the positioning of model bones, the translation error is less than *** and rotation error is less than 0.8°, when the deflection angle is less than 30°. And the translation error is 1.61mm and rotation error is 1.98°, when the angle reached 60°. It meets the requirements for PTED positioning, and has improved the positioning accuracy. © 2023 IEEE.

关键词： Errors

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Research on UAV Online Visual Tracking Algorithm based on YOLOv5 and FlowNet2 for Apple Yield Inspection 4

Research on UAV Online Visual Tracking Algorithm based on YO...

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4th world robot conference (wrc) / symposium on advanced robotics and automation (sara)

作者： Wang, Shaopeng Zhang, Xiaodong Shen, Haiming Tian, Minxuan Li, Mingyang Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Res Ctr Smart Agr Technol & Equipment Sch Mech Engn Xian 710049 Shaanxi Peoples R China

ISBN: (数字)9781665463690

ISBN: (纸本)9781665463690

Accurate monitoring of fruit quantity in apple orchards will allow growers to manage their orchards more efficiently, leading to higher yields. In addition, the rapid and accurate inspection of fruit in the orchard is also one of the basic technologies needed for smart agriculture. this paper proposes a real-time method for apple tracking and yield estimation. UAV carrying RGB camera is used as an inspection platform, which analyzes the video in real time during the inspection. the algorithm is built according to the Tracking-by-Detecting framework, where YOLOV5 target detection model is used to obtain apples' exact position. Meanwhile, the apples' position in next frame is estimated according to the optical flow calculated from FlowNet2 model. then, the predicted position and detected position is matched by the Hungarian algorithm. A dataset close to the actual situation in the orchard is constructed to verify the effectiveness of the proposed method. To improve the detection accuracy of apple under actual scene, the data enhancement strategy of random occlusion and mosaic enhancement is used for model training. As a result, the accuracy of apple detection achieved by the algorithm in this paper is 85.5%, which is 11% higher than previous studies. Besides, it can keep well tracking of detected apples even under the influence of complex occlusion or other factors, and achieve an accuracy of 90.39% in apple yield estimation. More importantly, this algorithm can reach a speed of 20FPS on the experimental platform, which meets the real-time requirements of UAV inspection.

关键词： Training Visualization Target tracking Insects Inspection Prediction algorithms Real-time systems

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