Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region

This paper focuses on a real-time obstacle avoidance control method for vehicles using model predictive control (MPC). MPC can optimize the motion of the vehicle over a finite time horizon while satisfying various constraints such as vehicle dynamics, the road width and the steering range. However,...

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Autores principales: Kazuki KIMURA, Kenichiro NONAKA, Kazuma SEKIGUCHI
Formato: article
Lenguaje:EN
Publicado: The Japan Society of Mechanical Engineers 2015
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Acceso en línea:https://doaj.org/article/72e212cc5bc24845b35225b4a7898f48
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spelling oai:doaj.org-article:72e212cc5bc24845b35225b4a7898f482021-11-26T06:25:42ZReal-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region2187-974510.1299/mej.14-00568https://doaj.org/article/72e212cc5bc24845b35225b4a7898f482015-03-01T00:00:00Zhttps://www.jstage.jst.go.jp/article/mej/2/3/2_14-00568/_pdf/-char/enhttps://doaj.org/toc/2187-9745This paper focuses on a real-time obstacle avoidance control method for vehicles using model predictive control (MPC). MPC can optimize the motion of the vehicle over a finite time horizon while satisfying various constraints such as vehicle dynamics, the road width and the steering range. However, the computational cost is too large for conducting real-time control. In this paper, a collision avoidance is realized by MPC with constraints for avoiding prohibited regions represented as circles. We approximate this region into a half plane separated by the tangent of the prohibited region. By handling approximated regions as constraints of the road width of MPC, we can implement the collision avoidance algorithm into the controller without increasing the computational cost. Moreover, in order to reduce the computational effort, we transform the nonlinear vehicle dynamics into reduced order and linearizable subsystems called time-state control form (TSCF). The effectiveness of the proposed method is proved by comparative simulations with conventional method where artificial potential method is applied to MPC. In addition, we conduct two experiments using a 1/10 scale vehicle which is equipped with a laser range finder to execute obstacle detection and localization. We show that real-time control can be realized even if we use an on-board embedded CPU which runs at the frequency of 500MHz.Kazuki KIMURAKenichiro NONAKAKazuma SEKIGUCHIThe Japan Society of Mechanical Engineersarticlevehicle controlmodel predictive controlobstacle avoidancetime state control formfront steering vehicleobstacle detectionlaser range finderMechanical engineering and machineryTJ1-1570ENMechanical Engineering Journal, Vol 2, Iss 3, Pp 14-00568-14-00568 (2015)
institution DOAJ
collection DOAJ
language EN
topic vehicle control
model predictive control
obstacle avoidance
time state control form
front steering vehicle
obstacle detection
laser range finder
Mechanical engineering and machinery
TJ1-1570
spellingShingle vehicle control
model predictive control
obstacle avoidance
time state control form
front steering vehicle
obstacle detection
laser range finder
Mechanical engineering and machinery
TJ1-1570
Kazuki KIMURA
Kenichiro NONAKA
Kazuma SEKIGUCHI
Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
description This paper focuses on a real-time obstacle avoidance control method for vehicles using model predictive control (MPC). MPC can optimize the motion of the vehicle over a finite time horizon while satisfying various constraints such as vehicle dynamics, the road width and the steering range. However, the computational cost is too large for conducting real-time control. In this paper, a collision avoidance is realized by MPC with constraints for avoiding prohibited regions represented as circles. We approximate this region into a half plane separated by the tangent of the prohibited region. By handling approximated regions as constraints of the road width of MPC, we can implement the collision avoidance algorithm into the controller without increasing the computational cost. Moreover, in order to reduce the computational effort, we transform the nonlinear vehicle dynamics into reduced order and linearizable subsystems called time-state control form (TSCF). The effectiveness of the proposed method is proved by comparative simulations with conventional method where artificial potential method is applied to MPC. In addition, we conduct two experiments using a 1/10 scale vehicle which is equipped with a laser range finder to execute obstacle detection and localization. We show that real-time control can be realized even if we use an on-board embedded CPU which runs at the frequency of 500MHz.
format article
author Kazuki KIMURA
Kenichiro NONAKA
Kazuma SEKIGUCHI
author_facet Kazuki KIMURA
Kenichiro NONAKA
Kazuma SEKIGUCHI
author_sort Kazuki KIMURA
title Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
title_short Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
title_full Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
title_fullStr Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
title_full_unstemmed Real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
title_sort real-time model predictive obstacle avoidance control for vehicles with reduced computational effort using constraints of prohibited region
publisher The Japan Society of Mechanical Engineers
publishDate 2015
url https://doaj.org/article/72e212cc5bc24845b35225b4a7898f48
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AT kenichirononaka realtimemodelpredictiveobstacleavoidancecontrolforvehicleswithreducedcomputationaleffortusingconstraintsofprohibitedregion
AT kazumasekiguchi realtimemodelpredictiveobstacleavoidancecontrolforvehicleswithreducedcomputationaleffortusingconstraintsofprohibitedregion
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