Litcius/Paper detail

Model Predictive Control for a Mecanum-wheeled Robot Navigating among Obstacles

Iñigo Moreno-Caireta, Enric Celaya, Lluís Ros

2021IFAC-PapersOnLine21 citationsDOIOpen Access PDF

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.

Topics & Concepts

Model predictive controlRobotController (irrigation)Control theory (sociology)Control engineeringKinematicsObstacleAgile software developmentActuatorTrajectoryComputer scienceObstacle avoidanceEnergy (signal processing)EngineeringMobile robotControl (management)Artificial intelligenceMathematicsPolitical scienceSoftware engineeringPhysicsBiologyClassical mechanicsStatisticsAgronomyLawAstronomyControl and Dynamics of Mobile RobotsIterative Learning Control SystemsVehicle Dynamics and Control Systems