基于四旋翼无人机的网球男孩机器人设计与实现

Yingze Lin, Liang Han, J. Liu
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引用次数: 0

摘要

随着网球赛事的不断发展,网球球童(tennis Ball Boy, TBB)机制逐渐完善,鹰眼视觉系统在网球赛事中的应用也日趋成熟,网球球童也逐渐走向智能化。本文提出了智能TBB机器人系统的概念,并针对网球比赛中TBB站位工作时间长、强度大、安全隐患大的问题,研制了基于四旋翼无人机的TBB机器人。基于模块化设计方法,智能TBB机器人包括机器人硬件设计、视觉网球目标检测、视觉定位与导航、机器人整体控制系统设计。网球夹紧机构是基于对称单自由度爪形机构设计的。网球目标检测系统采用YOLOX深度学习目标检测框架进行设计,该模型通过OpenVINO平台进行部署,使机器人能够实时检测网球。利用双目视觉融合IMU构建了基于VINS-FUSION框架的视觉定位系统。在此基础上,开发了SE(3)位置控制器、3D a *路径规划算法和Minimum Snap轨迹优化,使机器人具有导航和避障功能。针对机器人操作系统(ROS)平台,设计了一种基于有限状态机(FSM)的高级决策控制系统。最后,通过实验验证了机器人各模块的可靠性,为本文的进一步研究提供了依据。
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Design and Implementation of Tennis Ball Boy Robot Based on a Quadrotor UAV
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.
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