For planning rearrangements of objects in a clutter, it is required to know the goal configuration of the objects. However, in real life scenarios, this information is not available most of the time. We introduce a novel method that computes a collision-free placement of objects on a cluttered surface, while minimizing the total number and amount of displacements of the existing moveable objects. Our method applies nested local searches that perform multi-objective optimizations guided by heuristics. Experimental evaluations demonstrate high computational efficiency and success rate of our method, as well as good quality of solutions.
@article{arxiv.1906.08494,
title = {Object Placement on Cluttered Surfaces: A Nested Local Search Approach},
author = {Abdul Rahman Dabbour and Esra Erdem and Volkan Patoglu},
journal= {arXiv preprint arXiv:1906.08494},
year = {2019}
}