基于HS光流法的机器人避障策略优化

机器人的自主避障功能是其在未知环境中顺利行驶的最基本的功能，针对使用光流法进行机器人避障时，机器人因盲目避障、过早障碍而造成的避障效率低的问题，提出了优化避障策略的方法。在两轮式机器人上搭建实验平台，采用Horn&Schunck（HS）光流算法计算机器人运行前方的光流场，由光流场中信息来计算机器人与障碍物的碰撞时间TTC（Time to Contact），根据碰撞时间设计机器人的避障系统。通过在真实环境下进行的避障实验，验证了避障系统的有效性，并提出将机器人避障时的旋转角度与光流矢量值 的大小建立关系，从而更加合理高效的避开障碍物。

Obstacle Avoidance Strategy Optimization Based on HS Optical Flow for Mobile Robots

Autonomous obstacle avoidance of robot is the most basic function when it moves in an unknown environment. Aiming at the problem of obstacle avoidance due to blind obstacle avoidance and premature obstacle, the method of avoiding obstacle avoidance is put forward. The Horn & Schunck (HS) optical flow algorithm is used to calculate the optical flow field in front of the robot. The collision time TTC (Time to Contact) between the robot and the obstacle is calculated from the information of the optical flow field then designing the Obstacle Avoidance System by TTC. The effectiveness of the obstacle avoidance system is verified by the obstacle avoidance test in the real environment, and the relationship between the rotation angle and the value of the optical flow vector is put forward, and the obstacle can be avoided more rationally and efficiently.