基于多传感器融合的全向室内移动机器人系统研究

Xiangquan Tan, Shuliang Zhang, Qingwen Wu
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引用次数: 1

摘要

室内移动机器人面临着环境复杂、障碍物多、空间狭窄、导航精度低等问题。本文建立了基于多传感器融合的全向室内移动机器人系统,该系统由移动机器人本体、上阶控制系统和下阶控制系统组成。移动机器人本体是采用机械轮作作动机构的平台。上阶控制系统由上位机控制器和控制器上的机器人操作系统(ROS)组成。低阶控制系统由以STM32F103芯片为核心的机箱控制器、直流电机和编码器组成。通过激光雷达、超宽带、里程表和IMU等传感器的数据实现导航和定位功能。上阶控制系统首先对来自多个传感器的导航和定位数据进行融合和编程,然后向下阶控制系统发送指令;低阶移动控制系统接收这些控制指令并求解运动学模型,然后利用PID算法对机器人本体进行控制。建立了全向室内移动机器人的定位与导航测试环境。实验结果表明,基于多传感器融合的全向室内移动机器人系统具有全向室内移动能力强、避障能力强、定位导航精度高等优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Omnidirectional Indoor Mobile Robot System Based on Multi-sensor Fusion
Indoor mobile robot faces the problems such as complex situations, multiple barriers, narrow spaces and low navigation accuracy. In this paper, omnidirectional indoor mobile robot system based on multi-sensor fusion is established which consists of mobile robot body, upper order control system and lower order control system. The mobile robot body is a platform adopting mecanum wheels as actuating mechanism. The upper order control system consists of upper computer controllers and robot operating system (ROS) above the controllers. The lower order control system consists of chassis controller using STM32F103 chip as the core part, DC motors and encoders. The navigation and localization function are implemented by data of sensor such as laser radar, UWB, odometer and IMU. The upper order control system first fuses and programs the navigation and localization data from multiple sensors, then sends instructions to the lower order control system; the lower order mobile control system receives these control instructions and solves the kinematic model, then control the robot body using PID algorithm. Localization and navigation test environment of the omnidirectional indoor mobile robot is established. Experimental results show that localization and navigation of omnidirectional indoor mobile robot system based on multi-sensor fusion has the advantages of omnidirectional indoor mobile ability, strong barrier avoiding ability, and high localization and navigation accuracy.
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