为了克服传统机器人设计方法存在的局限性 ,提高机器人的自适应能力 ,采用神经网络方法实现了进化机器人避碰、趋近及其组合行为学习 .首先 ,提出了新的机器人模拟环境和机器人模型 ,给出了采用神经网络实现进化学习系统的方法 .其次 ,对具有进化学习机制的机器人基本行为和组合行为学习系统进行了仿真 ,并通过仿真证明了新模型不要求环境知识的完备性 ,机器人具有环境自适应学习能力 ,还具有结构简洁、易扩展等特点 .最后 ,对仿真结果进行分析与讨论 ,并指出了进一步研究方向 In order to overcome the limitations of the traditional robot design methods and improve the adaptive ability of robots, neural network method is used to avoid collision, approach and combination behavior of evolutionary robots.Firstly, a new robot simulation environment and robot model are proposed, The method of using neural network to realize evolution learning system is given.Secondly, the basic behavior and learning behavior of learning system with evolutionary learning mechanism are simulated, and the simulation results show that the new model does not require the completeness of environmental knowledge, Environmental adaptive learning ability, but also has the characteristics of simple structure, easy expansion, etc. Finally, the simulation results are analyzed and discussed, and pointed out further research directions