自治式水下机器人避障行为机制研究

Research on obstacle avoidance behavior for AUV

针对未知环境下自治式水下机器人(AUV)的运动规划问题,提出了一种基于行为的避障和趋向目标方法。根据行为动力学原理,设计了水平方面的趋向目标行为模块和避障行为模块,利用水平面的宏行为实现了水平面行为模块的融合。垂直面的行为设计根据模糊理论建立了输入"深度"和"高度"的模糊隶属度,制定了航行深度和距底高度与参考深度之间的推理规则,再通过解模糊化得到实际的参考深度的精确量。仿真结果表明:所设计的行为模型对外界环境有较好的反应性,响应正确有效,有助于提高AUV对环境的适应性。

Aimed at the problems of motion planning for autonomous underwater vehicle （AUV） in unknown environment, a behavior-based approach of obstacle avoidance and goal approaching is raised. Behavior dynamics is applied to design the goal approaching module and obstacle avoidance module. Using the macro behavior, behavior modules in the horizontal plane are fused. As to the behavior design in the vertical plane ,fuzzy theory is applied to construct the fuzzy membership function for the input ＂depth＂ and ＂height＂, to establish the reasoning rules obtaining the referenced depth from the input sailing depth and the height to the bottom and further to get a practical exact referenced depth by fuzzification. Simulation results show that the behavioral model has a better correct and effective response to the external environment, and is helpful to improve the adaptability of AUV to the environment.