An Improved Rapidly Exploring Random Tree Algorithm for Path Planning in Configuration Spaces with Narrow Channels

• Main Authors: Noel, Mathew Mithra, Chawla, Akshay
• Format: Journal Article
• Language: English
• Published: 01-11-2024
• Subjects: Computer Science - Robotics; Computer Science - Systems and Control
• DOI: 10.48550/arxiv.2411.00357

Rapidly-exploring Random Tree (RRT) algorithms have been applied successfully
to challenging robot motion planning and under-actuated nonlinear control
problems. However a fundamental limitation of the RRT approach is the slow
convergence in configuration spaces with narrow channels because of the small
probability of generating test points inside narrow channels. This paper
presents an improved RRT algorithm that takes advantage of narrow channels
between the initial and goal states to find shorter paths by improving the
exploration of narrow regions in the configuration space. The proposed
algorithm detects the presence of narrow channel by checking for collision of
neighborhood points with the infeasible set and attempts to add points within
narrow channels with a predetermined bias. This approach is compared with the
classical RRT and its variants on a variety of benchmark planning problems.
Simulation results indicate that the algorithm presented in this paper computes
a significantly shorter path in spaces with narrow channels.