Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives

Abstract

This work proposes a motion planning algorithm for robotic manipulators that combines sampling-based and search-based planning methods. The core contribution of the proposed approach is the usage of burs of free configuration space ($\mathcal{C}$-space) as adaptive motion primitives within the graph search algorithm. Due to their feature to adaptively expand in free $\mathcal{C}$-space, burs enable more efficient exploration of the configuration space compared to fixed-sized motion primitives, significantly reducing the time to find a valid path and the number of required expansions. The algorithm is implemented within the existing SMPL (Search-Based Motion Planning Library) library and evaluated through a series of different scenarios involving manipulators with varying number of degrees-of-freedom (DoF) and environment complexity. Results demonstrate that the bur-based approach outperforms fixed-primitive planning in complex scenarios, particularly for high DoF manipulators, while achieving comparable performance in simpler scenarios.

Authors 4

1. Benjamin Kraljušić

   University of Sarajevo

   Affiliation as printed

   University of Sarajevo,Faculty of Electrical Engineering,Bosnia and Herzegovina

2. Zlatan Ajanović Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Germany

3. Nermin Čović

   University of Sarajevo

   Affiliation as printed

   University of Sarajevo,Faculty of Electrical Engineering,Bosnia and Herzegovina

4. Bakir Lačević

   University of Sarajevo

   Affiliation as printed

   University of Sarajevo,Faculty of Electrical Engineering,Bosnia and Herzegovina