基于RGB-D SLAM的智能车自主避障与路径规划试验研究

Experimental Research on Autonomous Obstacle Avoidance and Path Planning of Intelligent Vehicle Based on RGB-D SLAM Technology

针对GPS信号弱、导航数据缺失场景下自主移动车辆难以精准定位的问题,采用即时定位与地图构建(SLAM)技术实现未知环境下无人小车地图构建与自主定位功能,采用动态A*算法实现了无人小车的避障与路径规划。分别进行了验证试验和未知环境下局部路径规划及全局路径规划试验,结果表明,提出的方案能有效地控制小车自主规划路径,避开障碍物到达目的地。

In order to solve the problem that it is difficult for autonomous mobile vehicles to accurately locate in scenarios with weak GPS signals and missing navigation data,Simultaneous Localization and Mapping(SLAM)technology is employed to realize the map and autonomous positioning function of the unmanned car in unknown environments,and the dynamic A*algorithm is used to realize the obstacle avoidance and path planning of the unmanned car.Verification experiments,local path planning under unknown environment and global path planning experiments are carried out respectively.The results show that the scheme proposed in this paper can effectively control the autonomous planning of the car to avoid obstacles to reach the destination.