东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (12): 1745-1748+1769.DOI: -

• 论著 • 上一篇    下一篇

基于模糊聚类判别的挖掘机器人行为控制

王福斌;刘杰;陈至坤;焦春旺;   

  1. 东北大学机械工程与自动化学院;河北联合大学电气工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(50775029);;

Behavior control of excavator robot based on fuzzy clustering discrimination

Wang, Fu-Bin (1); Liu, Jie (1); Chen, Zhi-Kun (2); Jiao, Chun-Wang (1)   

  1. (1) School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China; (2) Electrical Engineering College, Hebei United University, Tangshan 063009, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Wang, F.-B.
  • About author:-
  • Supported by:
    -

摘要: 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.

关键词: 挖掘机器人, 模糊聚类, 特征提取, 状态流, 行为控制

Abstract: 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.

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