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Obstacles Avoidance Based on Switching Potential Functions
DOI:10.1007/s10846-017-0687-2.png)
摘要
En 中文
In this paper, a novel path planning and obstacles avoidance method for a mobile robot is proposed. This method makes use of a switching strategy between the attractive potential of the target and a new helicoidal potential field which allows to bypass an obstacle by driving the robot around it. The new technique aims at overcoming the local minima problems of the well-known artificial potentials method, caused by the summation of two (or more) potential fields. In fact, in the proposed approach, only a single potential is used at a time. The resulting proposed technique uses only local information and ensures high robustness, in terms of achieved performance and computational complexity, w.r.t. the number of obstacles. Numerical simulations, together with comparisons with existing methods, confirm a very robust behavior of the method, also in the case of a framework with multiple obstacles.
Keyword:
Path planning
Obstacles avoidance
Artificial potentials method
Finite-time control
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期刊
J
IF:
2.8
论文数:
3.9K
被引数:
6.9K
机构
引用论文
An efficient neural network approach to dynamic robot motion planning一种用于动态机器人运动规划的有效神经网络方法
NEURAL NETWORKS
IF6.3
Local Path Planning for Off-oad Autonomous Driving With Avoidance of Static Obstacles避免静态障碍物的非自主驾驶的局部路径规划

