权重系数对基于光流法机器人避障系统的影响

基于光流法的机器人避障系统是近些年研究的新热点,为了实现机器人在未知环境下的自我避障功能,同时提高机器人的避障准确度,本文将对基于Horn-Schunck光流法的机器人避障系统进行研究,提出通过选取算法中合适的权重系数来提高机器人的避障效果。首先,运用HS算法建立真实的机器人避障系统,然后,在实验室中的Optitrack系统下进行真实的避障实验,并比较在不同的权重系数下机器人的避障效果,最终,通过实验结果得出：权重系数的取值会对机器人的避障效果产生影响,当权重系数取值在350,400]时,机器人的避障效果达到最优。

Weight Coefficient Influence on Robot Avoidance Obstacle System Based on Optical Flow Method

Robot avoidance obstacle system based on optical flow method is a new exploration point. In order to realize the self-avoiding function of the robot in the unknown environment and improve the obstacle avoidance accuracy of the robot, obstacle avoidance system will be researched through selecting the appropriate weight coefficient in the algorithm. First, the real robot obstacle avoidance system is established by using HS algorithm. Then the real obstacle avoidance experiment is carried out under the Optitrack system in the laboratory, and the obstacle avoidance effect under different weight coefficients will be compared. Finally, results of experiments show that the value of the weight coefficient has influences on the obstacle avoidance effect of the robot, and the obstacle avoidance effect of the robot is optimal when the weight coefficient is 350,400].