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For planning rearrangements of objects in a clutter, it is required to knowthe goal configuration of the objects. However, in real life scenarios, thisinformation is not available most of the time. We introduce a novel method thatcomputes a collision-free placement of objects on a cluttered surface, whileminimizing the total number and amount of displacements of the existingmoveable objects. Our method applies nested local searches that performmulti-objective optimizations guided by heuristics. Experimental evaluationsdemonstrate high computational efficiency and success rate of our method, aswell as good quality of solutions.

Object Placement on Cluttered Surfaces: A Nested Local Search Approach