Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks

S. Aydin; H. Temeltas

doi:10.1109/ISIE.2003.1267273

Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks

S. Aydin, H. Temeltas

Department of Control and Automation Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Citations (Scopus)

Abstract

A method is presented and tested for planning time optimal trajectories for a mobile robot with constraints by using an evolutionary technique with neural-networks components. The method establishes shortest time trajectories redefined to form a multi-constrained non-linear global optimization problem. The trajectory components such as the turning translational speeds of the mobile robot (i.e. the parameter vector of the problem) are found by using differential evolution algorithm (DE) to obtain the time optimally. DE is a floating-point genetic algorithm. Artificial neural networks learn kinematics structure and upper bound of the velocities on the trajectory. Experiments are successfully implemented on Nomad 2000 mobile robot.

Original language	English
Title of host publication	2003 IEEE International Symposium on Industrial Electronics, ISIE 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	352-357
Number of pages	6
ISBN (Electronic)	0780379128
DOIs	https://doi.org/10.1109/ISIE.2003.1267273
Publication status	Published - 2003
Event	IEEE International Symposium on Industrial Electronics, ISIE 2003 - Rio de Janeiro, Brazil Duration: 9 Jun 2003 → 11 Jun 2003

Publication series

Name	IEEE International Symposium on Industrial Electronics
Volume	I

Conference

Conference	IEEE International Symposium on Industrial Electronics, ISIE 2003
Country/Territory	Brazil
City	Rio de Janeiro
Period	9/06/03 → 11/06/03

Bibliographical note

Publisher Copyright:
© 2003 IEEE.

Keywords

Artificial neural networks
Genetic algorithms
Kinematics
Mobile robots
Neural networks
Optimization methods
Testing
Trajectory
Turning
Upper bound

Access to Document

10.1109/ISIE.2003.1267273

Cite this

Aydin, S., & Temeltas, H. (2003). Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks. In 2003 IEEE International Symposium on Industrial Electronics, ISIE 2003 (pp. 352-357). Article 1267273 (IEEE International Symposium on Industrial Electronics; Vol. I). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2003.1267273

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abstract = "A method is presented and tested for planning time optimal trajectories for a mobile robot with constraints by using an evolutionary technique with neural-networks components. The method establishes shortest time trajectories redefined to form a multi-constrained non-linear global optimization problem. The trajectory components such as the turning translational speeds of the mobile robot (i.e. the parameter vector of the problem) are found by using differential evolution algorithm (DE) to obtain the time optimally. DE is a floating-point genetic algorithm. Artificial neural networks learn kinematics structure and upper bound of the velocities on the trajectory. Experiments are successfully implemented on Nomad 2000 mobile robot.",

keywords = "Artificial neural networks, Genetic algorithms, Kinematics, Mobile robots, Neural networks, Optimization methods, Testing, Trajectory, Turning, Upper bound",

author = "S. Aydin and H. Temeltas",

note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; IEEE International Symposium on Industrial Electronics, ISIE 2003 ; Conference date: 09-06-2003 Through 11-06-2003",

year = "2003",

doi = "10.1109/ISIE.2003.1267273",

language = "English",

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Aydin, S & Temeltas, H 2003, Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks. in 2003 IEEE International Symposium on Industrial Electronics, ISIE 2003., 1267273, IEEE International Symposium on Industrial Electronics, vol. I, Institute of Electrical and Electronics Engineers Inc., pp. 352-357, IEEE International Symposium on Industrial Electronics, ISIE 2003, Rio de Janeiro, Brazil, 9/06/03. https://doi.org/10.1109/ISIE.2003.1267273

Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks. / Aydin, S.; Temeltas, H.
2003 IEEE International Symposium on Industrial Electronics, ISIE 2003. Institute of Electrical and Electronics Engineers Inc., 2003. p. 352-357 1267273 (IEEE International Symposium on Industrial Electronics; Vol. I).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - A method is presented and tested for planning time optimal trajectories for a mobile robot with constraints by using an evolutionary technique with neural-networks components. The method establishes shortest time trajectories redefined to form a multi-constrained non-linear global optimization problem. The trajectory components such as the turning translational speeds of the mobile robot (i.e. the parameter vector of the problem) are found by using differential evolution algorithm (DE) to obtain the time optimally. DE is a floating-point genetic algorithm. Artificial neural networks learn kinematics structure and upper bound of the velocities on the trajectory. Experiments are successfully implemented on Nomad 2000 mobile robot.

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KW - Optimization methods

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KW - Upper bound

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Aydin S, Temeltas H. Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks. In 2003 IEEE International Symposium on Industrial Electronics, ISIE 2003. Institute of Electrical and Electronics Engineers Inc. 2003. p. 352-357. 1267273. (IEEE International Symposium on Industrial Electronics). doi: 10.1109/ISIE.2003.1267273

Time optimal trajectory planning for mobile robots by differential evolution algorithm and neural networks

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Keywords

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