2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)最新文献_第7页

Scale Force Control of a Robot Bearing Augmentation Exoskeleton 机器人轴承增强外骨骼的比例力控制

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536125

Lin Lang, Hui Peng, Junhao Xiao, Huimin Lu, Zongtan Zhou

引用次数: 0

Solder Joint Inspection Using Imaginary Part of Gabor Features 利用Gabor虚部特征检测焊点

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536158

Hao Wu, Tianya You, Xiangrong Xu, A. Rodic, P. Petrovic

引用次数: 3

Deep Koopman Operator Based Model Predictive Control for Nonlinear Robotics Systems 基于深度Koopman算子的非线性机器人系统模型预测控制

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536053

Xuefeng Wang, Yu Kang, Yang Cao

{"title":"Deep Koopman Operator Based Model Predictive Control for Nonlinear Robotics Systems","authors":"Xuefeng Wang, Yu Kang, Yang Cao","doi":"10.1109/ICARM52023.2021.9536053","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536053","url":null,"abstract":"Modeling and control of nonlinear robotic systems have been challenging tasks. If a linear approximate embed-ding space for nonlinear dynamical robotic systems can be constructed, well-established techniques in the field of linear systems are expected to be used to deal with this problem. The Koopman theory suggests that a data-driven approach can be used to construct a suitable set of observation functions to map the nonlinear system into an equivalent linear model in the embedding space. We use deep neural networks to construct more adaptive sets of observation functions, treat the control inputs as generalized states, learn the input-Koopman operator of the controlled nonlinear robotic system, and construct the embedded linear state model DKoopman-predictor. The learned linear state model is then used to design the model prediction controller (DKoopman-MPC) to control the original nonlinear robotic system. The proposed approach is easy to implement and is data-driven without the need for a priori knowledge of model dynamics. Our experiments on mobile robot modeling and control show that the proposed method has higher model fidelity than existing local linearization methods, achieving 79.27% error reduction in the prediction task and has good convergence properties in the control task.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129134839","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: 3

Reliability Evaluation Method for Meta-action Unit Based on the All Fault Modes 基于全故障模式的元动作单元可靠性评估方法

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536110

Zongyi Mu, Y. Ran, Genbao Zhang, Guangqi Ying

{"title":"Reliability Evaluation Method for Meta-action Unit Based on the All Fault Modes","authors":"Zongyi Mu, Y. Ran, Genbao Zhang, Guangqi Ying","doi":"10.1109/ICARM52023.2021.9536110","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536110","url":null,"abstract":"Design for key Meta-action unit is an effective method to reduce the design difficulty of mechanical products. Reliability is an important design index for the Meta-action unit. Traditional reliability evaluation method evaluates the Meta-action unit’s reliability through the fault data after it fails. It means that traditional reliability evaluation method cannot evaluate the Meta-action unit’s reliability during its running process and provide reference for the initial design or reliability condition monitoring. To solve the above problems, this paper evaluated the Meta-action unit’s reliability by using the running data on the basis of its all fault modes. In this paper, firstly, the mechanical system is decomposed by FMA decomposition method and the Meta-action units of the mechanical system is obtained. Then, reliability of the Meta-action unit is evaluated by combining its all fault modes and running data. The reliability evaluation method based on all fault modes can provides references for the initial design and reliability condition monitoring of the Meta-action unit.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129853813","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

Dynamical Movement Primitives of Crossing over Obstacles for a Lower-Limb Prosthesis 下肢假体跨越障碍物的动态运动原语

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536102

Tao Zhang, Zhijun Li, Qinjian Li, Ying Feng

{"title":"Dynamical Movement Primitives of Crossing over Obstacles for a Lower-Limb Prosthesis","authors":"Tao Zhang, Zhijun Li, Qinjian Li, Ying Feng","doi":"10.1109/ICARM52023.2021.9536102","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536102","url":null,"abstract":"This paper proposes a trajectory generation of prosthesis to help amputee crossing over obstacles. Dynamical movement primitives (DMPs) are popular methods of reproducing trajectory for learning control. In the basic of DMPs, a novel term of obstacle is added to generate the trajectory in real-time. This term includes multiple point obstacle sources to reflect spatial size of obstacles. Each point obstacle is used to calculate direction relative to current position. Moreover, the direction vector and velocity vector are considered into term of obstacle. Besides, DMPs can generate effective trajectory through obstacle term parameter adjusting regardless of the obstacles in the front, middle or behind position in a step. Therefore, our method solves the inability crossing over obstacles under some scenarios and helps the prosthesis adapt to the various environment. Gaussian mixture regression is used to conjunction with DMPs for movement representation, which can reproduce new trajectory from multiple sets of original trajectories. Finally, simulations for DMPs were performed to demonstrate the flexibility of DMPs with obstacle term, which can generate desired trajectory of crossing over obstacles in various situations, indicating our method has a potential to facilitating prosthesis motion control.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126372882","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: 1

Person Counting Based On Graph Relation Network Using UAV 基于图关系网络的无人机人员计数

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536114

Ting-Bo Chen, Wenlian Huang, Xiaonan Hu, Zun Liu, Jie Chen, Zhuangzhuang Chen, Jianqiang Li, Junxin Liu, Xiao-Fan Ye

引用次数: 0

The Planar Force Perception on Robotic Bipolar Forceps 机器人双极钳的平面力感知

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536085

Xiuheng Zhang, Heng Zhang, Zhen Li, Guibin Bian

{"title":"The Planar Force Perception on Robotic Bipolar Forceps","authors":"Xiuheng Zhang, Heng Zhang, Zhen Li, Guibin Bian","doi":"10.1109/ICARM52023.2021.9536085","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536085","url":null,"abstract":"In neurosurgery, bipolar forceps is used to coagulate and dissect brain tissues. As in robot-assisted neurosurgical scenario, force perception on bipolar forceps can quantify intraoperative contacting forces between tips of forceps and brain tissues. The quantified tool-tissue contacting force information can help quantify experts experience and ensure safety of robot-assisted surgery. It is challengeable to facilitate the forceps with forces sensing ability because of the limited space for installing sensors. The craniocerebral tissues, interstitial fluids and currents passing though polar of forceps also bring restrictions on force sensing methods. In this article, we propose a planar force perception method to collect force information on bipolar forceps tips in real-time by installing two Fiber Bragg Grating Sensors (FBGs) perpendicularly on each polar of bipolar forceps. FBGs are free from electromagnetic interference. The slim configuration and silicon materials of FBGs make it a suitable sensing method for little disturbance on working state of bipolar forceps. In experiments, axial forces and planar forces were monitored in real-time. It is possible to sense forces at a minimum of 0.01 N. The calibrating revolution on x, y axis is 0.01, 0.03 N, separately.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124299728","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: 3

A Design Approach of 3D Optimal Mobile Sensor Array for Confidence-box based Tracking of a Magnetic Capsule 基于置信度盒的磁胶囊三维最优移动传感器阵列设计方法

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536121

Yangxin Xu, Keyu Li, Ziqi Zhao, M. Meng

引用次数: 0

Hybrid Obstacle-Surmounting Gait for Hexapod Wheel-Legged Robot in Special Terrain 特殊地形下六足轮腿机器人混合越障步态研究

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536128

Ruoxing Wang, Zhihua Chen, Kang Xu, Shou-kun Wang, Junzheng Wang, Bin Li

引用次数: 7

Research on the Algorithm of Target Location in Aerial Images under a Large Inclination Angle 大倾角航拍图像中目标定位算法研究

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI: 10.1109/ICARM52023.2021.9536160

Yu Chen, Xinde Li, S. Ge

引用次数: 2