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Time-optimal interception of objects moving along predictable paths

机译:沿可预测路径移动的物体的时间最佳拦截

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This paper focuses on planning strategies for object-interception, within the context of an active prediction planning and execution (APPE) strategy. Herein, the goal is to bring the robot end-effector to a pre-grasping location, so that a fine-motion grasping-strategy can be used. This objective is optimized within the APPE strategy by solving two problems: (i) selection of an optimal rendezvous-point; and, (ii) planning of a time-optimal robot-trajectory to this rendezvous-point. Problem (i), addressed herein, is formulated as a minimization of the robot-target interception-time. An adaptive-planning algorithm is proposed, where only the exact amount of computation time required is used to find the optimal rendezvous-point. Within this strategy, uncertainties must be expected and tolerated. The level of uncertainty provides a convergence constraint for the planning algorithm. The operation of this planning strategy is demonstrated via computer simulation. Experimental work using this approach is also cited.
机译:本文重点介绍了在活动预测规划和执行(APPE)策略的上下文中的对象拦截的规划策略。这里,目标是将机器人末端执行器带到预先抓握位置,从而可以使用微动抓握策略。通过解决两个问题:(i)选择最佳的聚集点,在Appe策略中进行了优化;而且(ii)规划该合约点的时间最佳的机器人轨迹。本文解决的问题(i)被配制成最小化机器人目标拦截时间。提出了一种自适应规划算法,其中仅使用所需的确切计算时间量来查找最佳的Rendezvous点。在此战略中,必须预期和容忍不确定性。不确定性水平为规划算法提供了收敛约束。通过计算机仿真证明了该规划策略的操作。还引用了使用这种方法的实验工作。

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