多个关节机器人分布式协作运动规划

Distributed Cooperative Motion Planning for Multiple Articulated Robots

  • 摘要: 由多个关节自治机器人构成的协作系统具有高度非线性和严重耦合性,为此提出了分布式协作运动规划方法(DCMP).应用大系统理论的分解协调方法,通过预估协调变量,解耦协作运动规划问题,使其分解为各个机器人个体的独立子规划,得到能够分布式迭代计算的子系统优化模型.利用协同进化算法在全局优化和约束条件处理方面的优势,DCMP解决高维组合C空间的空间—时间优化搜索问题、静态和动态约束问题,尤其是其它方法难以克服的速度约束问题.仿真实验结果证明了本文方法的有效性.

     

    Abstract: A distributed cooperative motion planning method(DCMP) is proposed for the cooperative system of multiple autonomous articulated robots,which is a severe nonlinear coupling system.The decoupling cooperative motion planning problem can be decomposed into several independent subplanning of each robot by the predictive coordination variables and a decomposition-coordination method for large scale system theory.And a subsystem optimization model which can be calculated in a distributly iterative manner is obtained.Taking advantages of its global optimization characteristics and the constraint handling capability,the DCMP method solves several problems,including space-time optimization search in high-dimensional combined C-space and static-dynamic constraints handling,especially the velocity constraint problem which other methods are difficult to overcome.Simulations experiment result shows the effectiveness of the proposed method.

     

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