Evolutionary multiple path planner for assembly

Abstract

The problem of assembly operation feasibility is considered as a hierarchy of feasibility tests: local feasibility and global feasibility. We consider the problem of global feasibility as a multi-dimensional optimization problem which is approached using evolutionary computation techniques. A novel, iterative, multiresolution path representation is used as a basis for the evolutionary coding. If a successful path is found early in the search hierarchy (at a low level of resolution), then further expansion of that portion of the path search is not necessary. This advantage is mapped into the encoded search space and adjusts the path resolution accordingly. The algorithm can accommodate different optimization criteria, changes in these criteria, and is capable of finding multiple, alternative paths simultaneously. The effectiveness of the algorithm is demonstrated on a number of multi-dimensional path planning problems for assembly.