Adaptation Algorithm of Geometric Graphs for Robot Motion Planning in Dynamic Environments

Abstract

This study proposes an adaptive graph algorithm for collision-free motion planning of articulated robots in dynamic environments. For this purpose, deformations of the configuration space were analyzed according to the changes of the workspace using various simulations. Subsequently, we adopted the principles of gas motion dynamics in our adaptation algorithm to address the issue of the deformation of the configuration space. The proposed algorithm has an adaptation mechanism based on expansive repulsion and sensory repulsion, and it can be performed to provide the entire adaptation using distributed processing. The simulation results confirmed that the proposed method allows the adaptation of the roadmap graph to changes of the configuration space.

Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning

“…This paper proposes an algorithm to optimize the roadmap graph that can cover arbitrary morphologies of the free configuration space to maximize coverage. Our previous study [23] considered an adaptation algorithm for geometric graphs in an intuitive manner. However, in this study, we reanalyze that adaptive graph algorithm and present its results in terms of the maximization of graph coverage.…”