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We examine an important combinatorial challenge in clearing clutter using amobile robot equipped with a manipulator, seeking to compute an optimal objectremoval sequence for minimizing the task completion time, assuming that eachobject 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 whenno two objects to be removed have any overlap. Then, we constructasymptotically optimal and heuristic algorithms for clutter removal. Employingdynamic programming, our optimal algorithm scales to 40 objects. On the otherhand, for random clutter, fast greedy algorithms tend to produce solutionscomparable to these generated by the optimal algorithm.

Taming Combinatorial Challenges in Optimal Clutter Removal Tasks