文章基本信息

标题：The Path Planning of AUV Based on D-S Information Fusion Map Building and Bio-Inspired Neural Network in Unknown Dynamic Environment
作者：Daqi Zhu ; Weichong Li ; Mingzhong Yan 等
期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2014
卷号：11
期号：3
页码：34
DOI：10.5772/56346
语种：English
出版社：SAGE Publications
摘要：In this paper a biologically inspired neural dynamics and map planning based approach are simultaneously proposed for AUV (Autonomous Underwater Vehicle) path planning and obstacle avoidance in an unknown dynamic environment. Firstly the readings of an ultrasonic sensor are fused into the map using the D-S (Dempster-Shafer) inference rule and a two-dimensional occupancy grid map is built. Secondly the dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation. The AUV path is autonomously generated from the dynamic activity landscape of the neural network and previous AUV location. Finally, simulation results show high quality path optimization and obstacle avoidance behaviour for the AUV.
关键词：AUV (Autonomous Underwater Vehicle); Map Building; D-S Information Fusion; Path Planning; Biologically Inspired Neural Dynamics; Neural Network; Obstacle Avoidance