SP-NN: A novel neural network approach for path planning
Shuai Li, Max Q.‐H. Meng, Wanming Chen, Yangming Li, Zhu‐Hong You, Yajin Zhou, Lei Sun, Huawei Liang, Kai Jiang, Qinglei Guo · 2007
In this paper, a neural network approach named shortest path neural networks (SP-NN) is proposed for real-time on-line path planning. Based on grid-based map and mapping this kind of map to neural networks, this proposed method is capable of generating the globally shortest path from the target position to the start position without collision with any obstacles. The dynamics of each neuron is distinctive to other previously presented methods by other researchers and ensures that the generated path is shortest without collision and that the state of neurons varied continuously. Extensive simulations show the efficiency of the presented method.