Publication

Model predictive control for a Mecanum-wheeled robot navigating among obstacles

Conference Article

Conference

IFAC Conference on Nonlinear Model Predictive Control (NMPC)

Edition

2021

Pages

119-125

Doc link

https://doi.org/10.1016/j.ifacol.2021.08.533

File

Download the digital copy of the doc pdf document

Abstract

Mecanum-wheeled robots have been thoroughly used to automate tasks in many different applications. However, they are usually controlled by neglecting their dynamics and relying only on their kinematic model. In this paper, we model the behaviour of such robots by taking into account both their equations of motion and the electrodynamic response of their actuators, including dry and viscous friction at their shafts. This allows us to design a model predictive controller aimed to minimise the energy consumed by the robot. The controller also satisfies a number of non-linear inequalities modelling motor voltage limits and obstacle avoidance constraints. The result is an agile controller that can quickly adapt to changes in the environment, while generating fast and energy-efficient manoeuvres towards the goal.

Categories

automation, control theory, optimisation.

Author keywords

dynamic modeling, omnidirectional wheeled robots, model predictive control, motion control, trajectory planning, optimization, obstacle avoidance, energy efficiency, Mecanum wheel

Scientific reference

I. Moreno, E. Celaya and L. Ros. Model predictive control for a Mecanum-wheeled robot navigating among obstacles, 2021 IFAC Conference on Nonlinear Model Predictive Control, 2021, Bratislava, pp. 119-125.