未知环境下机器人避障设计研究

Design of Robot Obstacle Avoidance in Unknown Environment

随着信息技术的发展,各个领域越来越需要高性能的自动化系统。机器人技术飞速发展,研究重点已经转向在复杂、未知、不可预测环境中独立工作的自主式智能机器人。介绍了机器人Q学习避障算法的实现方法,并构建了仿真实验平台,模拟了移动机器人在未知环境下自主地、安全地从起始点到达目标点的过程。通过仿真实验验证了Q学习实现机器人在未知环境下的行为选择控制是可行的、有效的,并验证机器人在未知环境下具有良好的越障性能。

With the development of information technology, high-performance automation systems are increasingly required in various fields. With rapid development of robotics technology, research focus has been shifted to autonomous intelligent robots working independently in a complex, unknown, unpredictable environment.It describes the Q-learning algorithm to achieve obstacle avoidance methods, and build a simulation platform to simulate the process of a mobile robot reaching the target from the starting point independently and safely in unknown environment. The simulation experiments validate that the control over a robot＇s choice of behavior in unknown environment through Q-learning is feasible and effective, and verify that a robot has a good performance on obstacle crossing in unknown environment.