Rearrangement Planning of Multiple Movable Objects by a Mobile Robot
Rearrangement Planning of Multiple Movable Objects by a Mobile Robot
复制标题
移动机器人对多个可移动物体的重新排列规划
DOI：
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发表时间：
2009
期刊：
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通讯作者：
J. Ota
中科院分区：
文献类型：
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作者：
J. Ota
针对某类重排问题，提出了一种移动的机器人对多个可移动物体的重排规划方法，LP ε k（k > 2）问题。由于机器人搬运操作，几个物体将从初始配置移动到单独的目的地。提出了一种由全局运动规划器和局部运动规划器组成的运动规划算法。全局规划器使用可移动物体的优先图，而局部规划器使用称为LRTA*（学习实时A*）的实时搜索方法。局部规划器中的两个重要因素是中间配置的生成和启发式函数的设计。在四个、七个和十个可移动物体的重排模拟中，对每个因素中的三种方法进行了比较。该方法从任务完成时间的角度证明了该算法的有效性。两种规划器的计算代价均与一次激活的可移动目标数成多项式关系。仿真结果表明，所提出的算法可以实际应用，虽然不完整，重排问题，最多约10个可移动的对象。
A rearrangement planning methodology of multiple movable objects by a mobile robot is proposed for a certain rearrangement problem, i.e., the LP ε k (k > 2) problem. Several objects are to be moved from an initial configuration to separate destinations as a result of a robot handling operation. Proposed in this paper is a planning algorithm consisting of a global motion planner and a local motion planner. The global planner uses a precedence graph of a movable object, while the local planner uses a real-time search methodology called LRTA* (Learning Real-Time A*). Two important factors in the local planner are the generation of intermediate configurations and the design of heuristic functions. Three methods in each factor are compared in the rearrangement simulation of four, seven and 10 movable objects. The proposed method demonstrates the effectiveness of the proposed algorithm from the viewpoint of task completion time. The calculation costs for both planners are polynomial with the number of movable objects for one time activation. Simulation results indicate that the proposed algorithm can be practically applied, although not complete, to rearrangement problems with, at most, about 10 movable objects.