2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)最新文献_第7页

Design of the robotic system for natural orifice transluminal endoscopic surgery in urology 泌尿外科自然腔口内镜手术机器人系统的设计

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872228

Xiongpeng Shu, Qi Chen, Peng Hua, Shuang Wang, Ling Zhang, Le Xie

引用次数: 0

Sample-data Consensus of Position Synchronization in Static Directed Networks 静态有向网络中位置同步的样本数据一致性

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872262

Yi Lu, Ji Huang, Zhenlong Xiao, Xin Wang, Desheng Zhang

引用次数: 0

Multi-Direction Decoding of Both-Hand Movement Using EEG Signals 基于脑电信号的双手运动多方向解码

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872187

Run Gao, Yingchi Liu, Jiarong Wang, Luzheng Bi

引用次数: 0

Fast Adaptation Dynamics Model for Robot’s Damage Recovery 机器人损伤恢复的快速自适应动力学模型

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872230

Ci Chen, Dongqi Wang, Jiyu Yu, Pingyu Xiang, Haojian Lu, Yue Wang, R. Xiong

{"title":"Fast Adaptation Dynamics Model for Robot’s Damage Recovery","authors":"Ci Chen, Dongqi Wang, Jiyu Yu, Pingyu Xiang, Haojian Lu, Yue Wang, R. Xiong","doi":"10.1109/RCAR54675.2022.9872230","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872230","url":null,"abstract":"In the process of operating, robots will inevitably encounter damage due to external or internal factors, such as motors blockage. For the legged robot, when the motors of joints are failing, if other motors still act according to the original instructions, it will cause the robot to deviate from the predetermined trajectory, which is unacceptable for legged robots. Inspired by the fact that the model trained by supervised learning on the training set can be generalized to the testing set, our goal is to obtain a dynamic model that can be generalized to all kinds of motor damage situations. It can predict what state will be reached in the next step when an action is applied in the current state. With this dynamics model, we use the Monte Carlo particles to optimize the feasible actions in a model predictive control (MPC) fashion and achieve the expected goal (such as making the robot walk in a straight line). The comparison experiment adopt two meta-learning model and vanilla dynamics model approaches, the results show that the proposed method is superior to the three baselines, which proves the effectiveness of the proposed method.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130675101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Manipulative Control Algorithm of Moxibustion Robot Based on 6-DOF Manipulator 基于六自由度机械手的艾灸机器人操作控制算法

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872222

Shanming Bai, Juan Cui, Zhidong Zhang, Yongqiu Zheng, Chenyang Xue

{"title":"Manipulative Control Algorithm of Moxibustion Robot Based on 6-DOF Manipulator","authors":"Shanming Bai, Juan Cui, Zhidong Zhang, Yongqiu Zheng, Chenyang Xue","doi":"10.1109/RCAR54675.2022.9872222","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872222","url":null,"abstract":"The burden of doctors is heavy and the consumption of medical supplies is large in the process of traditional moxibustion treatment. Currently, the robot that can replace doctors to complete moxibustion treatment has a simple structure, low degree of freedom and intelligence, and only completes simple operation control at fixed points. Hence, there is still a lack of moxibustion robots that can realistically simulate moxibustion techniques with complex angles. In this paper, a trajectory planning algorithm for moxibustion manipulations is designed based on the 6-DOF manipulator. The robot can complete the collection of acupuncture points, which in different directions of the human body, and truly reproduce the complex and changeable moxibustion techniques. It can realize the precise control and intelligent transformation of different techniques in the treatment process. At the same time, the robot combines temperature monitoring and feedback system. It makes therapy of robot more realistic, friendlier and improves the safety of mechanical arm. Finally, the feasibility and accuracy of the robot are verified by system test. The moxibustion auxiliary robot is not only expected to be used for professional physiotherapy in hospitals, but also can be promoted to individual users for realizing the family self-help physiotherapy model, and has broad market and application prospects.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125008453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Image Segmentation Based on An Improved Pulse Coupled Neural Network for Atomic Force Microscopy 基于改进脉冲耦合神经网络的原子力显微镜图像分割

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872210

Ying Chang, Yinan Wu, Yongchun Fang, Zhi Fan

引用次数: 0

Biped Robots’ Push Recovery based on Viscoelastic Model* 基于粘弹性模型的两足机器人推力恢复研究*

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872202

Jiaheng Du, Xuechao Chen, Lianqiang Han, Qingqing Li, Zhifa Gao, Zhangguo Yu

{"title":"Biped Robots’ Push Recovery based on Viscoelastic Model*","authors":"Jiaheng Du, Xuechao Chen, Lianqiang Han, Qingqing Li, Zhifa Gao, Zhangguo Yu","doi":"10.1109/RCAR54675.2022.9872202","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872202","url":null,"abstract":"Biped robots have great practical value. High stability and anti-disturbance ability are the prerequisites for the practical applications of biped robots. For standing stability research, the current methods could be roughly divided into three groups: ankle strategy, hip strategy, step strategy. For the first two strategies, the virtual model control method is always used. However, many above methods adopt virtual spring damping model as the basic control model, which is too stiff and lacks flexibility. Therefore, the robots controlled by the virtual spring damping model may be easy to fall down when the disturbance is large. To solve the problem of spring damping model’s poor performance while dealing with large disturbance, the viscoelastic model is introduced in this paper, and this paper proposes a control algorithm for the underactuated biped robot to stand stably and resist disturbance in the two-dimensional environment. The new algorithm makes the robot perform a higher flexibility. The method includes the construction of linear quadratic regulator(LQR) with using viscoelastic model, the use of LQR controller to control the stable standing of biped robot and the realization of anti-disturbance function, etc. The comparsion simulations prove the better performance of the virtual viscoelastic model than the virtual spring damping model. The validity and effectiveness of the algorithm are verified through experiments.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121281337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Upper Limb Multi-Joint Angle Estimation Based on Multichannel sEMG Signals Using Elman Neural Network 基于多通道表面肌电信号的Elman神经网络上肢多关节角度估计

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872197

Yongbai Liu, Gang-Yi Wang, Zhenda Tian, Keping Liu, Zhongbo Sun

{"title":"Upper Limb Multi-Joint Angle Estimation Based on Multichannel sEMG Signals Using Elman Neural Network","authors":"Yongbai Liu, Gang-Yi Wang, Zhenda Tian, Keping Liu, Zhongbo Sun","doi":"10.1109/RCAR54675.2022.9872197","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872197","url":null,"abstract":"Continuous motion angle estimation based on surface electromyography (sEMG) signals is a significant part of human active motion intention recognition, which plays an crucial effect in the aspect of natural human-robot interaction and rehabilitation therapy. In this paper, to predict the upper limb multi-joint angle based on multichannel sEMG signals, the Elman neural network model (ELNN) is applied and investigated to estimate upper limb multi-joint motion angle from multichannel sEMG signals under different motion modes of the upper limbs. Specifically, the sEMG signals of anterior deltoid (AD), posterior deltoid (PD), biceps brachii (BB), triceps brachii (TB), extensor carpi radialis (ECR) and flexor carpi radialis (FCR) will be collected and preprocessed, then, the ELNN model based on multichannel sEMG signals is employed to predict the multi-joint motion angles of the upper limbs including shoulder, elbow and wrist. Theoretical analysis, experimental results and root-mean-square error (RMSE) analysis indicate that the presented ELNN model has better prediction accuracy and dynamic characteristics than BP network in continuous estimation of upper limb multi-joint motion angle.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"563 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116203379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study on Intelligent Metering Platform Based on Cloud Computing 基于云计算的智能计量平台研究

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872268

Xinyi Li, H. Sun, Chen Chen, X. Ou, Tianqiang Dong, Hongzhong Zhang

引用次数: 0

Control of Fixed-wing UAV Using Optimized PID Controller with the Adaptive Genetic Algorithm 基于自适应遗传算法优化PID控制器的固定翼无人机控制

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872224

Xincheng Yu, Lirong Yan, Zhizhou Guan, Yibo Wu, Fuming Peng, Fuwu Yan

{"title":"Control of Fixed-wing UAV Using Optimized PID Controller with the Adaptive Genetic Algorithm","authors":"Xincheng Yu, Lirong Yan, Zhizhou Guan, Yibo Wu, Fuming Peng, Fuwu Yan","doi":"10.1109/RCAR54675.2022.9872224","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872224","url":null,"abstract":"Aiming at the time-varying and nonlinear problems of fixed-wing unmanned aerial vehicle (UAV) system, a UAV flight control algorithm was proposed based on PID control algorithm and the adaptive genetic algorithm (GA). On the basis of the traditional algorithm, the settling time was considered as the influencing factors of the objective function. The optimal index was determined by using the overshoot, rise time and settling time of the system response as variables, and adjusting the corresponding weight according to the actual situation to change the system response result. Moreover, the crossover probability and mutation probability in GA could be adaptively changed, so that the optimal parameters in the PID control process could be quickly and accurately found. Based on the rigid body dynamics model and kinematic model of the fixed-wing UAV, the simulation models of five control loops were designed in MATLAB/Simulink, namely the pitch angle, roll angle, yaw angle, speed and height control loops. Compared with the traditional PID controller, the system responses of the five control loops were significantly improved with faster response speed, and less than 5% overshoot. The proposed algorithm had strong adaptability and anti-interference ability.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128086687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0