基于改进RBPF算法的轮式机器人SLAM导航系统设计

传统的机器人导航系统在复杂的地形环境中常常无法引导机器人躲避突然出现的障碍物，无法精准采集数据。为此提出一种改进RBPF算法的轮式机器人SLAM导航系统，对系统硬件和软件进行设计。系统硬件主要由导航功能模块、底盘驱动模块、控制模块组成，利用RPLIDAR A1型激光测距雷达设计导航功能模块，并设计底盘驱动模块和控制模块。软件设计中，以改进RBPF算法为基础，设计了轮式机器人SLAM导航系统的实现程序，应用算法代入的方式加强了普通轮式机器人导航算法对粒子计算与卡尔曼滤波的敏感程度。实验结果表明，改进RBPF算法在避障和计算误差方面的优势，证明了该系统相比传统避障后的路径选择更便捷，导航错误出现率降低了30%左右。

Design of Wheeled Robot SLAM Navigation System Based on Improved RBPF Algorithm

Traditional robot navigation systems often fail to guide robots to avoid sudden obstacles in complex terrain environments, and cannot accurately collect data. To this end, a wheeled robot SLAM navigation system with improved RBPF algorithm is proposed, and the system hardware and software are designed. The system hardware is mainly composed of navigation function modules, chassis drive modules, and control modules. The RPLIDAR A1 laser ranging radar is used to design navigation function modules, and chassis drive modules and control modules are designed. In the software design, based on the improved RBPF algorithm, the implementation program of the wheeled robot SLAM navigation system is designed, and the method of applying algorithm substitution enhances the sensitivity of the ordinary wheeled robot navigation algorithm to particle calculation and Kalman filtering. The experimental results show that the improved RBPF algorithm has advantages in obstacle avoidance and calculation errors, which proves that the system is more convenient than traditional path selection after obstacle avoidance, and the navigation error rate is reduced by about 30%.