Publication
Model predictive control for a Mecanum-wheeled robot navigating among obstacles
Conference Article
Conference
IFAC Conference on Nonlinear Model Predictive Control (NMPC)
Edition
7th
Pages
119-125
Doc link
https://doi.org/10.1016/j.ifacol.2021.08.533
File
Authors
Projects associated
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, 7th IFAC Conference on Nonlinear Model Predictive Control, 2021, Bratislava, Slovakia, pp. 119-125.
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