Composition of dynamic roadmaps for dual-arm motion planning

Abstract

Dynamic roadmaps (DRM) are a planning approach for robots in changing environments where fast replanning is required. DRMs are based on a precomputed graph in the configuration space and mappings from workspace voxels to vertices and edges in the graph, which allows for computation times below 100 ms. While dynamic roadmaps can in principle be applied to dual-arm motion planning, it may be beneficial to use independent roadmaps per arm. This paper proposes four different approaches for planning based on two separate DRMs that all take advantage of the availability of workspace mappings. A sequential approach first plans for a prioritized arm and then considers its motion as obstacle for the second arm. The other three planners coordinate the motion of the arms along fixed paths or graphs such that no collision occurs. Benchmarks are performed for two robot models with different ratios of overlapping workspace to investigate the pros and cons of the composition approaches and to compare them to a single roadmap for the dual-arm robot.