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首次讨论了基于案例的学习方法在自主式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自主式水下机器人的全局路径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．
It is the first time to discuss the application of case-based learning in the autonomous global path planning of underwater robots. Case-based learning is an incremental learning process that learns and solves problems based on past experience. In this paper, the application framework of case-based learning in the global path planning of autonomous underwater robots is studied. Corresponding algorithms are proposed for the extraction of case attributes, the matching and selection of cases, and the updating of case bases. Finally, several sets of simulation results are given.