Real-time obstacle avoidance for car robot using potential field and local incremental planning

2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2014-05-14 DOI:10.1109/ECTICON.2014.6839898

Sittichai Boonyarak, P. Prempraneerach

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引用次数: 2

Abstract

Integration of local incremental planning and potential field is proposed for a motion planning of the car-like robot in this research so that obstacle avoidance and goal seeking could be achieved in real time. The feedback linearization control using a desired trajectory generated from the virtual force of potential function could help accomplishing these objectives. Both attractive and repulsive forces are function of both relative position and velocity between robot-obstacle and robot-target. The motion planning of the car-like robot has been demonstrated using this new local incremental planning when the unknown and dynamics environment contains either fixed multiple obstacles or moving obstacles. Results, demonstrated in Matlab simulation, reveal that the car-like robot can reach the target point and avoid moving obstacles at the same time, which could be implemented for a real car robot in near future.

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基于势场和局部增量规划的汽车机器人实时避障

本研究提出了将局部增量规划与势场相结合的类车机器人运动规划方法，实现了机器人的实时避障和目标寻优。利用势函数虚力产生的期望轨迹的反馈线性化控制可以帮助实现这些目标。引力和斥力都是机器人-障碍物和机器人-目标之间的相对位置和相对速度的函数。在未知和动态环境中包含多个固定障碍物或移动障碍物时，利用这种新的局部增量规划方法对类车机器人进行了运动规划。Matlab仿真结果表明，该仿车机器人可以同时到达目标点并避开移动障碍物，在不久的将来可以在真正的汽车机器人上实现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

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