Assembly planning is an important task for manufacturing industrial products. The ability to automate and optimize the process is crucial as it can improve the production time, cost and efficiency. In general, the planning procedure involves two main reasoning stages, one is based on geometric reasoning and the other is based on AI tree-search. In this article, a novel approach to automate the geometric reasoning stage for large assembly systems is proposed. This technique provides a fast and accurate measure of capturing feasible spatial interactions and relationships between elements of a CAD assembly with no manual interventions. These results are then used by a suite of AI planning tools to generate optimal assembly sequences. The algorithm has been tested on a variety of examples resembling real products and results show the efficiency and effectiveness of the algorithm.
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