• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2005, Vol. 27 ›› Issue (12): 72-75.

• 论文 • 上一篇    下一篇

基于神经网络的移动机器人路径规划

周宏志[1] 王伊卿[1] 樊长虹[2]   

  • 出版日期:2005-01-01 发布日期:2010-06-22

  • Online:2005-01-01 Published:2010-06-22

摘要:

针对移动机器人未知环境下的安全路径规划,本文采用了一种局部连接Hopfield神经网络(ANN)规划器。对任意形状环境,ANN中兼顾处理了“过近”和“过远”来形成安全  路径,而无需学习过程。为在单处理器上进行有效的在线路径规划,提出用基于距离变换的串行模拟,加速数值势场的传播。仿真表明,该方法具有较高的实时性和环境适 应性。

关键词: 移动机器人 安全路径规划 神经网络 约束距离变换

Abstract:

For the safe path planning of mobile robots in unknown environments, the paper proposes a locally linked Hopfield artificial neural network (ANN) pl anner. For the environments of arbitrary shape, without the learning process, ANN plans a safe path with the consideration of both“too close”and“too   far”. For the effective application on a single processor to plan a path on-line, the simulation based on constrained distance transformation is propo  osed to accelerate the propagation of the numerical potential field of ANN. Simulations demonstrate the method has high real-time ability and adaptabili ty to environments.

Key words: (mobile robot, safe path planning;neural networks;constrained distance transformation)