基于A^(*)算法和TEB算法的智能小车自主导航避障研究

Research on Automatic Navigation Obstacle Avoidance of Intelligent Car Based on A^(*) Algorithm and TEB Algorithm

在智能小车的控制系统中,小车周围的环境会随着车体的运动而不断地发生变化,从而影响智能小车下一步的运动控制。针对这一问题,论文设计了一种基于A^(*)算法和TEB算法的智能小车自主导航避障系统。该系统采用Jetson Nano作为核心控制器,运行Ubuntu 18.04系统,并安装有ROS机器人操作系统。同时,该系统选取STM32作为运动控制器的主控板,板上装备IMU,可以实现对四路直流电机的闭环操控。智能小车利用激光雷达不断地扫描周围的环境,采用IMU与轮式里程计融合定位的方法,获取融合滤波后的里程计信息,从而实现智能小车的自主导航避障功能。最后,通过数值仿真和实验调试对所提方法进行验证,结果表明该系统能有效精确地定位,并实现自主导航与避障。

In the control system of intelligent car,the environment changes constantly with the movement of the intelligent car,which affects the next movement control of the intelligent car.To solve this problem,an automatic navigation obstacle avoid-ance system for intelligent car based on A^(*)algorithm and TEB algorithm is designed.Jetson Nano is regarded as the core controller of the system;it runs Ubuntu 18.04 system and installs the ROS robot operating system.At the same time,STM32 is selected as the main control board of motion controller of the system,the board is equipped with IMU,which can realize the closed-loop control of four DC motors.The lidar is used to scan the environment around the intelligent car continuously,and the fusion positioning ap-proach of IMU and wheel odometer is utilized to obtain the odometer information after fusion filtering,so that the automatic naviga-tion obstacle avoidance function of the intelligent car can be realized.Finally,the proposed method is verified by numerical simula-tion and experimental debugging.The obtained results show that the system can locate effectively and accurately,and achieve the function of autonomous navigation obstacle avoidance.