2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)最新文献_第9页

Payload Quantification via Proprioceptive-only Sensing for a Single-legged Vertical Hopper 单腿垂直料斗的本体感知载荷量化

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872248

Yu Zhang, Yongming Yue, Yingrong Chen, Haoyao Chen, Wei Gao, Shiwu Zhang

{"title":"Payload Quantification via Proprioceptive-only Sensing for a Single-legged Vertical Hopper","authors":"Yu Zhang, Yongming Yue, Yingrong Chen, Haoyao Chen, Wei Gao, Shiwu Zhang","doi":"10.1109/RCAR54675.2022.9872248","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872248","url":null,"abstract":"Legged robots, in their various applications, can be sent to carry a payload during their locomotion. However, carrying a payload without knowing its weight would potentially impede the robot’s locomotion performance. This paper focuses on payload quantification for legged robots driven by quasi-direct drive brushless DC motors. A single-legged vertical hopper has been used for proof of concept. Experimental data on the ground reaction force were collected through proprioceptive-only sensing on the physical platform and compared to the predictions generated by an extended Spring-Loaded Inverted Pendulum model. The Bayesian method is then used for inferring the payload parameter within the model. It is found that the assumption of massless leg in developing this kind of reduced-order models for legged locomotion make them particularly inaccurate at the moment of impact and the leg compressing period after that. As a result, using data from the leg decompressing period of the stance phase makes the quantification results more useful. This shed light on future implementation of this framework in a real-time manner.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"37 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":"133501498","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

Design and Validation of a Master-slave Continuum Robot for Maxillary Sinus Surgery 上颌窦手术主从连续机器人的设计与验证

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872272

Yongfeng Cao, Fan Feng, Zefeng Liu, Le Xie

引用次数: 1

The Research on the Identification of ACC SOTIF Triggering Conditions Based on Scenario Analysis 基于情景分析的ACC SOTIF触发条件识别研究

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/rcar54675.2022.9872207

Qidong Zhao, Zheng Tong, Yunshuang Zhang, Chen Chao, Qingyu Zhang, Shuai Zhao, Zhibin Du

引用次数: 1

Combining Clustering Undersample and Ensemble Learning for Wearable Fall Detection 基于下样本聚类和集成学习的可穿戴跌倒检测

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872285

Zhang Meng, Daoxiong Gong

{"title":"Combining Clustering Undersample and Ensemble Learning for Wearable Fall Detection","authors":"Zhang Meng, Daoxiong Gong","doi":"10.1109/RCAR54675.2022.9872285","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872285","url":null,"abstract":"Accidental falls often cause serious harm to the human body, especially for the elderly. But falls tend to be infrequent, making it difficult to collect large amounts of data for research. In reality, there is a large gap between the amount of sensor data collected by falling activities and daily activities, which will lead to class imbalance. When using machine learning algorithms to detect falls, class imbalance will cause the performance of the classifier to be biased towards most classes and reduce the detection accuracy of a few classes. When faced with the problem of binary class imbalance, selecting an effective machine learning algorithm and resampling data can effectively improve the accuracy of classification. In this paper, an ensemble learning algorithm and clustering undersampling method are used for fall detection. The ensemble learning algorithm can reduce the impact of imbalanced datasets on the training model through multiple classifier iterations. Clustering undersampling method can change the dataset distribution and balance the number of positive and negative samples. The method in this paper is evaluated on the public dataset Sisfall. Compared with the traditional machine learning algorithms, the ensemble learning has higher accuracy and faster training speed. Combined with the clustering undersampling method, the method has a higher recall and precision.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"20 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":"130085562","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

Pedestrian Detection Based on Improved Faster-RCNN Algorithm 基于改进Faster-RCNN算法的行人检测

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872220

Chunling Yang, Dong Qiu

引用次数: 0

Driving stability control of the carrier-borne aircraft traction system* 舰载机牵引系统驱动稳定性控制*

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872214

Z. Can, Hongbo Liu, X. Yang, Wenyao Han

引用次数: 0

Behavioral Dynamics-based Impedance Control for Collision Avoidance of Human-Following Robots 基于行为动力学的人类跟随机器人避碰阻抗控制

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872283

Haoyu Tian, Xin Ma

{"title":"Behavioral Dynamics-based Impedance Control for Collision Avoidance of Human-Following Robots","authors":"Haoyu Tian, Xin Ma","doi":"10.1109/RCAR54675.2022.9872283","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872283","url":null,"abstract":"Human-following is an important part of man-machine interaction and has wide application value. In Human-following, the following stability, human comfort and obstacle avoidance are considered comprehensively. To solve the above problems, we propose a human behavioral dynamics-based impedance control for collision avoidance of human-following robot, which take the comfort and the following stability into consideration. Specifically, an impedance control method combined with virtual interaction force is introduced to simulate the human social dynamic characteristics to improve the comfort of human-following. The uniformly ultimately bounded property of the impedance control is proved by using the Lyapunov stability theorem. Moreover, an obstacle component constructed by behavioral dynamics is proposed to extend the impedance controller for collision avoidance. Behavioral dynamics compared with an artificial potential field method possess better collision avoidance performance during humanfollowing. The simulation results validate that the human-following system integrated with collision avoidance is effective.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"35 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":"116007591","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: 2

Energy Shaping Based Nonlinear Anti-Swing Controller for Double-Pendulum Rotary Crane with Distributed-Mass Beams 基于能量整形的分布质量梁双摆回转起重机非线性抗摆控制

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872177

Gang Li, Xin Ma, Zhi Li, Yibin Li

{"title":"Energy Shaping Based Nonlinear Anti-Swing Controller for Double-Pendulum Rotary Crane with Distributed-Mass Beams","authors":"Gang Li, Xin Ma, Zhi Li, Yibin Li","doi":"10.1109/RCAR54675.2022.9872177","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872177","url":null,"abstract":"Rotary cranes usually transfer the heavy mass and large payloads with distributed mass beam in practice. As a typical underactuated system, the dynamic model is very complicated and challenging due to the actuated boom luffing motion and underactuated distributed mass beam payload swing vibration. To simplify the dynamic model, the existing control method regards the payload as the mass point, which ignores the geometry of the payload. This paper proposes an energy shaping based nonlinear anti-swing controller for double-pendulum rotary crane with distributed-mass beams. The rotary crane dynamic model is established based on the Lagrange’s method. After analysis the energy function, a nonlinear anti-swing controller is designed for the rotary crane. It successfully solves the boom positioning and payload anti-swing problems with a distributed mass beam payload. LaSalle’s invariance theorem and Lyapunov technology are helped to analysis the stability of the rotary crane control system. Finally, the proposed controller shows effective and robust control performance in the simulation verification.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"2 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":"114474303","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

RCAR 2022 Cover Page RCAR 2022封面

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/rcar54675.2022.9872155

引用次数: 0

Design and Implementation of Robot Middleware Service Integration Framework Based on DDS 基于DDS的机器人中间件服务集成框架的设计与实现

2022 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2022-07-17 DOI: 10.1109/RCAR54675.2022.9872212

Xiaowen Zhang, Xiaogang Zhang, Shaoyuan Wang, Xiao Ping

{"title":"Design and Implementation of Robot Middleware Service Integration Framework Based on DDS","authors":"Xiaowen Zhang, Xiaogang Zhang, Shaoyuan Wang, Xiao Ping","doi":"10.1109/RCAR54675.2022.9872212","DOIUrl":"https://doi.org/10.1109/RCAR54675.2022.9872212","url":null,"abstract":"The distributed real-time system composed of industrial robots usually needs to meet the support of low-latency, high-reliability data transmission and service invocation. Based on the Data Distribution Service (DDS) publish-subscribe communication paradigm, this paper designs a service integration framework model called Dynamic-DDS-RPC with a request-response mechanism to achieve low-latency and flexible configuration of the robot service remote procedure call function. First of all, we use JSON to implement a set of service description specifications to support service definition and program interface implementation, and uses dynamic library automatic loading technology to solve the problem that DDS-RPC does not support dynamic loading and discovery of services. Secondly, we implement a topic-centric service request-response mechanism based on the publish-subscribe communication mode of DDS, and realize low-latency data communication. Finally, we develop a robot middleware software based on the framework, and use the middleware to compare the performance of the service-request response speed with the WebService-based middleware and the DDS-RPC-based middleware. The results show that the service integration framework proposed in this paper can realize the remote procedure call function with low latency and high flexible configuration, which verifies the effectiveness of the framework.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"20 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":"114821709","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