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This paper introduces Backward Layout Search (BLS), a novel approach for robotic assembly layout planning that determines initial part poses in reverse order to ensure collision-free execution of a specified assembly sequence. By leveraging the dependency of assembly step feasibility on the poses of current and future parts, BLS incorporates geometric, kinematic, and motion checks, while utilizing collision masks and filtering to streamline candidate selection. Experimental results demonstrate that BLS not only generates executable layouts but also significantly reduces both step evaluations and search time compared to traditional forward search methods.
BLS cuts assembly planning time in half while ensuring collision-free execution, transforming how robots approach complex assembly tasks.
Robotic assembly layout planning must determine the assembly site and the initial pose of each part while ensuring collision-free execution of a prescribed assembly sequence. This problem is challenging because the obstacle environment changes after each assembly step, and unassembled parts re maining in the workspace may block robot motions. We observe that the feasibility of each assembly step depends only on the initial poses of the current and later-assembled parts. Based on this dependency, we propose Backward Layout Search (BLS), which assigns initial part poses in reverse assembly order. Each expansion performs geometric, kinematic, grasp, and prescribed-motion checks, while collision masks and candidate set filtering remove infeasible initial part pose candidates. Promising partial layouts are retained through beam selection, and complete layouts are validated by full motion planning in forward assembly order. Experiments on five assembly models show that BLS produces collision-free executable layouts and reduces step evaluations and search time compared with a matched forward search.
