Linear Time Varying MPC Based Path Planning of an Autonomous Vehicle via Convex Optimization
Publish place: Journal of Iranian Association of Electrical and Electronics Engineers، Vol: 14، Issue: 4
Publish Year: 1396
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JIAE-14-4_008
تاریخ نمایه سازی: 1 اردیبهشت 1397
Abstract:
In this paper a new method is introduced for path planning of an autonomous vehicle. In this method, the environment is considered cluttered and with some uncertainty sources. Thus, the state of detected objectshould be estimated using an optimal filter. To do so, the state distribution is assumed Gaussian. Thus the state vector is estimated by a Kalman filter at each time step. The estimation ofthe probabilistic distribution can be shown using an error ellipse for a constant collision probability. Analytical forms oferror ellipses can be obtained by quadratic inequalities. These quadratic inequalities make the optimization problem nonconvex. Thus, these inequalities are relaxed by applying a linearization approach. Finally, the optimization problem is reformulated to a convex optimization problem. There are some strong algorithms for solving a convex optimization problem, so the consequent path planning method can be solved efficiently with considerable performance that will be obtained in the end of this pape
Keywords:
Stochastic Path Planning , Path Planning Under Uncertainty , Linear Time-Varying MPC , Quadratic Programming , Error Ellipse , Convex Optimization
Authors
Mohsen Ahmadi Mousavi
Graduate Student of Mechatronics Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran
Behzad Moshiri
Professor,Control and Intelligent Processing Center of Excellence (CIPCE) , College of Engineering, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
zainabolhada heshmati
Assistant Professor, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran