在最优杂波消除任务中驯服组合挑战
Taming Combinatorial Challenges in Optimal Clutter Removal Tasks
摘要：
我们研究了一个重要的组合挑战，在清除杂波使用移动机器人配备了一个机械手，寻求计算最佳的对象删除序列最小化的任务完成时间，假设每个对象被抓住一次，然后随后删除。在结构方面，我们建立了这样一个最佳序列可以是NP-难计算，即使没有两个对象被删除有任何重叠。然后，我们构造了渐近最优和启发式的杂波去除算法。采用动态规划，我们的优化算法规模为40个对象。另一方面，对于随机杂波，快速贪心算法倾向于产生与最优算法产生的解可比的解。
英文摘要：
We examine an important combinatorial challenge in clearing clutter using a mobile robot equipped with a manipulator, seeking to compute an optimal object removal sequence for minimizing the task completion time, assuming that each object is grasped once and then subsequently removed. On the structural side, we establish that such an optimal sequence can be NP-hard to compute, even when no two objects to be removed have any overlap. Then, we construct asymptotically optimal and heuristic algorithms for clutter removal. Employing dynamic programming, our optimal algorithm scales to 40 objects. On the other hand, for random clutter, fast greedy algorithms tend to produce solutions comparable to these generated by the optimal algorithm.
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