Integration of an Inverse Optimal Neural Controller with Reinforced-SLAM for Path Panning and Mapping in Dynamic Environments

Authors

  • Alma Y. Alanis Universidad de Guadalajara, CUCEI
  • Nancy Arana-Daniel Universidad de Guadalajara, CUCEI
  • Carlos Lopez-Franco Universidad de Guadalajara, CUCEI
  • Edgar Guevara-Reyes Universidad de Guadalajara, CUCEI

DOI:

https://doi.org/10.13053/cys-19-3-2023

Keywords:

Optimal neural control, reinforced-SLAM, path panning, mapping, dynamic environments

Abstract

This work presents an artificial intelligence approach to solve the problem of finding a path and creating a map in unknown environments using Reinforcement Learning (RL) and Simultaneous Localization and Mapping (SLAM) for a differential mobile robot along with an optimal control system. We propose the integration of these approaches (two of the most widely used ones)  for the implementation of robot navigation systems with an efficient method of control composed by a neural identifier and an inverse optimal control in order to obtain a robust and autonomous system of navigation in unknown and dynamic environments.

Author Biographies

Alma Y. Alanis, Universidad de Guadalajara, CUCEI

Received the B.Sc. degree from Instituto Tecnologico de Durango (ITD), Durango Campus, Durango, Durango, in 2002, the M.Sc. and the Ph.D. degrees in Electrical Engineering from the Center of Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN), Guadalajara Campus, Mexico, in 2004 and 2007, respectively. Since 2008 she has been with the University of Guadalajara, where she is currently a Chair Professor at the Department of Computer Science and member of the Intelligent Systems Research Group.She is also a member of the Mexican National Research System (SNI-1). Her research interest centers on neural control, backstepping control, block control, and their applications to electrical machines, power systems, and robotics.

Nancy Arana-Daniel, Universidad de Guadalajara, CUCEI

Received the M.Sc. degree in Computer Science in 2003 and the Ph.D. in Computer Science in 2007, both from the Center of Research and Advanced Studies (CINVESTAV-IPN), Guadalajara Campus, Mexico. She is currently a research fellow at the Department of Computer Science of the University of Guadalajara, Mexico, where she works together with other researchers of the Intelligent Systems Research Group. Her research interests focus on applications of geometric algebra, machine learning, optimization,computer vision, pattern recognition, and visually guided robot navigation.

Carlos Lopez-Franco, Universidad de Guadalajara, CUCEI

Received the Ph.D. degree in Computer Science from the Center of Research and Advanced Studies (CINVESTAV-IPN), Mexico, in 2007. He is currently a professor at the Department of Computer Science of the University of Guadalajara, Mexico, and a member of the Intelligent Systems Research Group. His research interests include geometric algebra, computer vision, robotics, and intelligent systems.

Edgar Guevara-Reyes, Universidad de Guadalajara, CUCEI

Received the B.Sc. in Computer Engineering in 2011 and the M.Sc. in Electrical and Computer Engineering from the University of Guadalajara in 2014. His interests include optimal and adaptive control and neural network controllers for dynamic systems.

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Published

2015-09-30

Issue

Vol. 19 No. 3 (2015): 19(3) 2015 Thematic issue: Vision and Robotics (Guest editors: S. Ortega, A. Pedroza, O. Carbajal, B. Castillo Toledo)

Section

Articles

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