移动机器人在未知狭窄环境中的路径规划
Path Planning for Mobile Robot in Unknown Narrow Environments
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摘要: 在障碍物体积比较庞大,自由空间相对狭窄的未知环境中,人工势场法很容易产生反复、徘徊等现象.本文结合几何信息和参考方向来纠正人工势场法这些缺陷,实现在这类环境中的有目的的平滑的路径规划.并且提出一种能够适应复杂环境的避障策略.仿真结果证明了上述方法的有效性.Abstract: When the obstacles are large, or the free space is narrow, artificial potential field (APF) is prone to produce zigzag and wandering path. This paper combines the geometrical information and the reference direction to correct the shortcoming of APF, in order to plan a smooth and purposive path. This paper also develops an effective strategy with which the robot can advance even when it is surrounded by many obstacles.