A caster-wheel-aware MPC-based motion planner for mobile robotics

TL;DR

This paper introduces a caster-wheel-aware model predictive control approach for mobile robots that incorporates caster wheel dynamics into motion planning, improving efficiency and accuracy without extra sensors.

Contribution

It presents a novel caster-wheel-aware term for MPC-based control, along with an observer for caster wheel states, enhancing motion planning for robots with caster wheels.

Findings

Improved motion efficiency in intralogistics robots.

Caster wheel estimator performs well without additional sensors.

Outperforms decoupled bore-torque reduction methods.

Abstract

Differential drive mobile robots often use one or more caster wheels for balance. Caster wheels are appreciated for their ability to turn in any direction almost on the spot, allowing the robot to do the same and thereby greatly simplifying the motion planning and control. However, in aligning the caster wheels to the intended direction of motion they produce a so-called bore torque. As a result, additional motor torque is required to move the robot, which may in some cases exceed the motor capacity or compromise the motion planner's accuracy. Instead of taking a decoupled approach, where the navigation and disturbance rejection algorithms are separated, we propose to embed the caster wheel awareness into the motion planner. To do so, we present a caster-wheel-aware term that is compatible with MPC-based control methods, leveraging the existence of caster wheels in the motion planning stage. As a proof of concept, this term is combined with a a model-predictive trajectory tracking controller. Since this method requires knowledge of the caster wheel angle and rolling speed, an observer that estimates these states is also presented. The efficacy of the approach is shown in experiments on an intralogistics robot and compared against a decoupled bore-torque reduction approach and a caster-wheel agnostic controller. Moreover, the experiments show that the presented caster wheel estimator performs sufficiently well and therefore avoids the need for additional sensors.