Path-Parameterised RRTs for Underactuated Systems

TL;DR

This paper introduces a specialized RRT-based motion planning algorithm for underactuated systems that efficiently generates feasible, dynamically consistent paths and time parameterisations, outperforming existing methods in success rate and speed.

Contribution

The paper develops a novel path-parameterised RRT algorithm that simplifies dynamic feasibility checks and improves planning efficiency for underactuated systems.

Findings

Higher success rates in feasible trajectory computation

Lower mean computation times compared to existing approaches

Effective generation of both geometric paths and time parameterisations

Abstract

We present a sample-based motion planning algorithm specialised to a class of underactuated systems using path parameterisation. The structure this class presents under a path parameterisation enables the trivial computation of dynamic feasibility along a path. Using this, a specialised state-based steering mechanism within an RRT motion planning algorithm is developed, enabling the generation of both geometric paths and their time parameterisations without introducing excessive computational overhead. We find with two systems that our algorithm computes feasible trajectories with higher rates of success and lower mean computation times compared to existing approaches.