{"title":"Design and Implementation of Tennis Ball Boy Robot Based on a Quadrotor UAV","authors":"Yingze Lin, Liang Han, J. Liu","doi":"10.1109/CACRE58689.2023.10208124","DOIUrl":null,"url":null,"abstract":"With the continuous development of tennis tournaments, the Tennis Ball Boy (TBB) mechanism has been gradually improved, the Eagle-Eye Vision System has been maturely applied in tennis tournaments, and TBB has been moving towards intelligence. In this paper, the concept of an intelligent TBB robot system is proposed, and a TBB robot based on a quadrotor Unmanned Aerial Vehicle (UAV) is developed to address the problems of long working hours, high intensity and the safety hazards of standing for TBB in tennis tournaments. Based on the modular design method, the intelligent TBB robot includes robot hardware design, visual tennis ball object detection, visual localization and navigation, and overall robot control system design. The tennis ball clamping mechanism is designed based on a symmetric single Degree-Of-Freedom (DOF) pawl mechanism. The tennis ball object detection system is designed with the YOLOX deep learning object detection framework, and this model is deployed through the OpenVINO platform, which enables the robot to detect tennis balls in real-time. The visual localization system based on the VINS-FUSION framework is constructed with a binocular vision fusion IMU. On this basis, a SE(3) positional controller, a 3D A* path planning algorithm and Minimum Snap trajectory optimization are developed to enable the robot to have navigation and obstacle avoidance functions. An advanced decision control system based on the Finite State Machines (FSM) is designed for the Robot Operating System (ROS) platform. Finally, the experiment verifies the reliability of each module of the robot, and this paper can provide a basis for further research.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CACRE58689.2023.10208124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the continuous development of tennis tournaments, the Tennis Ball Boy (TBB) mechanism has been gradually improved, the Eagle-Eye Vision System has been maturely applied in tennis tournaments, and TBB has been moving towards intelligence. In this paper, the concept of an intelligent TBB robot system is proposed, and a TBB robot based on a quadrotor Unmanned Aerial Vehicle (UAV) is developed to address the problems of long working hours, high intensity and the safety hazards of standing for TBB in tennis tournaments. Based on the modular design method, the intelligent TBB robot includes robot hardware design, visual tennis ball object detection, visual localization and navigation, and overall robot control system design. The tennis ball clamping mechanism is designed based on a symmetric single Degree-Of-Freedom (DOF) pawl mechanism. The tennis ball object detection system is designed with the YOLOX deep learning object detection framework, and this model is deployed through the OpenVINO platform, which enables the robot to detect tennis balls in real-time. The visual localization system based on the VINS-FUSION framework is constructed with a binocular vision fusion IMU. On this basis, a SE(3) positional controller, a 3D A* path planning algorithm and Minimum Snap trajectory optimization are developed to enable the robot to have navigation and obstacle avoidance functions. An advanced decision control system based on the Finite State Machines (FSM) is designed for the Robot Operating System (ROS) platform. Finally, the experiment verifies the reliability of each module of the robot, and this paper can provide a basis for further research.