Open AccessModel predictive control for the tracking of autonomous mobile robot combined with a local path planning
Author(s) -
Jianhua Li,
Jianfeng Sun,
Liqun Liu,
Jianing Xu
Publication year - 2021
Publication title -
measurement + control/measurement and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.286
H-Index - 21
eISSN - 2051-8730
pISSN - 0020-2940
DOI - 10.1177/00202940211043070
Subject(s) - obstacle avoidance , model predictive control , trajectory , control theory (sociology) , mobile robot , obstacle , motion planning , computer science , pid controller , collision avoidance , controller (irrigation) , path (computing) , robot , tracking (education) , control engineering , collision , control (management) , simulation , engineering , artificial intelligence , pedagogy , computer security , law , temperature control , biology , psychology , political science , agronomy , programming language , physics , astronomy
This article presents a model predictive control (MPC) coupled with an artificial potential field (APF) to resolve the trajectory tracking while considering the obstacle avoidance. In this article, the obstacle avoidance problem is solved by a local path planning based on the artificial potential field by constructing a virtual goal. A virtual goal is generated to produce an attractive force to guide the mobile robot to a collision-free space. The planned path is controlled by a proportional–integral–derivative (PID) controller to avoid collision. After arriving at the virtual goal, an off-line explicit MPC is calculated to obtain the optimal control inputs to track the reference trajectory. The simulation results show that the proposed method can be applied to control the mobile robot in the environment with one obstacle.