自主式水下机器人全局路径规划的基于案例的学习算法研究

本文讨论了基于案例的学习方法在水下机器人全局路径规划中的应用问题．基于案例的学习方法是一种增量式的学习过程，它根据过去的经验进行学习及问题求解．本文对基于案例的学习方法在规划中的应用框架进行了初步研究，对案例属性的提取，案例的匹配和择优，以及案例库的更新等问题提出了相应的算法．最后给出了几组仿真结果．

AUV GLOBAL PATH PLANNING USING CASE BASED LEARNING ALGORITHM

This paper presents an AUV global path planning scheme using case based learning algorithm. Case based learning is relatively a new approach to path planning. Case based learning is learning and reasoning from past episodic information about the environment. A new and suitable solution is generated by retrieving and adapting and old one, which approximately matches the current situation. In this research, the algorithm includes these parts: establishment of path attribute extracted from its features, matching and retrieving case from the case library, and updating the case library. The effectiveness of the algorithm is verified through simulations.