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Mobile robot trajectory tracking using model predictive control

TLDR
In this article, the authors focus on the application of model-based predictive control (MPC) to the trajectory tracking problem of nonholonomic wheeled mobile robots (WMRs).
Abstract
This work focus on the application of model-based predictive control (MPC) to the trajectory tracking problem of nonholonomic wheeled mobile robots (WMR). The main motivation of the use of MPC in this case relies on its ability in considering, in a straightforward way, control a nd state constraints that naturally arise in practical proble ms. Furthermore, MPC techniques consider an explicit performance criterion to be minimized during the computation of the control law. The trajectory tracking problem is solved using two approaches: (1) nonlinear MPC and (2) linear MPC. Simulation results are provided in order to show the effectiveness of both schemes. Considerations regarding the computational effort of the MPC are developed with the purpose of analyzing the real-time implementation viability of the proposed techniques.

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Citations
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Journal ArticleDOI

An adaptive dynamic controller for autonomous mobile robot trajectory tracking

TL;DR: In this paper, an adaptive controller is proposed to guide an unicycle-like mobile robot during trajectory tracking, where the desired values of the linear and angular velocities are generated, considering only the kinematic model of the robot.
Journal ArticleDOI

Robust Constrained Learning-based NMPC enabling reliable mobile robot path tracking

TL;DR: The goal is to use learning to generate low-uncertainty, non-parametric models in situ that provide safe, conservative control during initial trials when model uncertainty is high and converges to high-performance, optimal control during later trials whenmodel uncertainty is reduced with experience.
Journal ArticleDOI

Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking

TL;DR: The results show that the system can start from a generic a priori vehicle model and subsequently learn to reduce vehicle- and trajectory-specific path-tracking errors based on experience, and be able to balance trial time, path- tracking errors, and localization reliability based on previous experience.
Journal ArticleDOI

Nonlinear Model Predictive Control for trajectory tracking and collision avoidance of underactuated vessels with disturbances

TL;DR: In this paper, a combined nonlinear model predictive control (NMPC) for position and velocity tracking of underactuated surface vessels, and collision avoidance of static and dynamic objects into a single control scheme with sideslip angle compensation and environmental disturbances counteraction is presented.
Proceedings ArticleDOI

Learning-based nonlinear model predictive control to improve vision-based mobile robot path-tracking in challenging outdoor environments

TL;DR: The results show that the system can start from a generic a priori vehicle model and subsequently learn to reduce vehicle- and trajectory-specific path-tracking errors based on experience, and be able to balance trial time, path- tracking errors, and localization reliability based on previous experience.
References
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Book

Model Predictive Control

TL;DR: In this article, the authors present a model predictive controller for a water heating system, which is based on the T Polynomial Process (TOP) model of the MPC.
Proceedings ArticleDOI

A stable tracking control method for an autonomous mobile robot

TL;DR: The control rule and limiting method proposed are robot independent and hence can be applied to various kinds of mobile robots with a dead reckoning ability and was implemented on the autonomous mobile robot Yamabico-11.
Journal ArticleDOI

A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability

TL;DR: It is proved that feasibility of the open-loop optimal control problem at time t = 0 implies asymptotic stability of the closed-loop system.
Journal ArticleDOI

Structural properties and classification of kinematic and dynamic models of wheeled mobile robots

TL;DR: The structure of the kinematic and dynamic models of wheeled mobile robots is analyzed and it is shown that, for a large class of possible configurations, they can be classified into five types, characterized by generic structures of the model equations.
Journal ArticleDOI

Exponential stabilization of mobile robots with nonholonomic constraints

TL;DR: In this paper, an exponentially stable controller for a two-degree-of-freedom robot with nonholonomic constraints is presented, which is shown to be nonstabilizable via pure smooth feedback.
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