基于模糊聚类判别的挖掘机器人行为控制

Behavior Control of Excavator Robot Based on Fuzzy Clustering Discrimination

为实现挖掘机器人的自主挖掘,构建了适合挖掘机器人的行为控制体系结构.以挖掘行为作为基准,用状态流模型实现挖掘目标、挖掘任务、挖掘行为的逐层分解.采集目标图像、机械臂倾角及液压缸压力信号,作为状态流行为状态之间触发转换的事件或条件.针对挖掘中遇到的沙土物料、表面块状物料、块状物料埋于沙中3种挖掘环境,综合视觉定位信息、压力及倾角信息,通过模糊聚类判别后,触发挖掘动作状态流模型,有区别地自主处理挖掘中遇到的不同情况.最后通过控制挖掘动作,实现自主挖掘目标.

In order to realize the autonomy excavation of excavator robot,the behavior control system architecture was built.With the excavation behavior as a baseline,the state-flow model was used to implement the excavation object,the excavation task and the excavation behavior stepwise.The object image,rake angle of mechanical arm and pressure signal of hydraulic cylinder were collected,as the event and condition for trigger and transition between behavior states of state-flow.According to the three kinds of mining environment during the excavation,which are sand,surface block material and block material buried in sand,the visual position,pressure and rake angle information were gathered and mining action state-flow model was triggered after the fuzzy clustering discrimination,then the different circumstances encountered in mining were processed distinguishingly and independently.Finally the autonomy excavation object was achieved by controlling excavation action.