Multi-stage warm started optimal motion planning for over-actuated mobile platforms

TL;DR

This paper introduces a lightweight, multi-stage motion planning method for over-actuated mobile platforms that efficiently generates feasible trajectories considering non-linearities and constraints, demonstrated on a planetary rover.

Contribution

It proposes a novel multi-stage warm-start approach combining Fast Marching and sequential LQ regulators for optimal motion planning of complex mobile platforms.

Findings

Speeds up computation time significantly.

Increases success ratio for sample retrieval missions.

Successfully tested on ESA's Exomars Rover.

Abstract

This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers non-linearities and constraints. The proposed motion planner is based on a sequential multi-stage approach that takes advantage of the warm start on each step. Firstly, a globally optimal and smooth 2D/3D trajectory is generated using the Fast Marching Method. This trajectory is fed as a warm start to a sequential linear quadratic regulator that is able to generate an optimal motion plan without constraints for all the platform actuators. Finally, a feasible motion plan is generated considering the constraints defined in the model. In this respect, the sequential linear quadratic regulator is employed again, taking the previously generated unconstrained motion plan as a warm start. This novel approach has been deployed into the Exomars Testing Rover of the European Space Agency. This rover is an Ackermann-capable planetary exploration testbed that is equipped with a robotic arm. Several experiments were carried out demonstrating that the proposed approach speeds up the computation time, increasing the success ratio for a martian sample retrieval mission, which can be considered as a representative use case of an over-actuated mobile platform.