一种针对VFH系列算法阈值敏感问题的改进策略
An improved strategy for VFH threshold sensitive problem

针对VFH系列算法的阈值敏感问题，提出了一种新的自适应阈值改进策略.综合考虑移动机器人硬件特性、运动特性和目标点环境设置初始阈值、确定阈值范围.使用阈值评价函数，对可选范围内的每组阈值与可通行方向进行综合评价，使得机器人能够实时选取适合当前情况的阈值.最后在ROS上实现算法，并使用EAI移动机器人平台进行多次对比实验.实验结果证明，使用自适应阈值改进策略后，机器人能够避免局部死区，并在目标周围存在障碍物时，以较短的无碰撞平滑路径顺利到达目标位置.
In view of the threshold sensitive problem of VFH series algorithms，a new adaptive threshold improvement strategy is proposed. First the initial threshold and the threshold range is determined by the hardware，motion characteristics of the robot and the target environment. Then, a threshold evaluation function is used to comprehensively evaluate each threshold and accessible direction in the optional range，so that the robot can get the threshold suitable for the current situation in real time. Finally，the algorithm is realized in ROS，and several comparative experiments are conducted using the EAI mobile robot platform. The experimental results show that when the improved policy with adaptive threshold is applied，the robot can avoid local dead zone and successfully reach the target position in complex environment, especially when the target is surrounded with obstacles