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Razavi Asfali S A. Control And Path Planning Of AUVs Robot Using Krill Herd Optimization Algorithm And Learning Automata. sjfst 2020; 2 (2) :1-8
URL: http://sjfst.srpub.org/article-6-48-en.html
URL: http://sjfst.srpub.org/article-6-48-en.html
Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Abstract: (1517 Views)
In this study first, we investigated the equations in movement of an underwater robot and also the state-space model of system is expressed with linearizing existing equations. Then, an energy efficient path is planned using dynamic equations and dynamic planning optimization method. There are moving obstacles in environment in which a robot is moving. It can be seen that the planned path is flat and energy consumption is minimized. The main objective of the study is to present an appropriate controller for the provided state-space model of system. For this purpose, by studying the system controller designing using LQR optimal controller, an appropriate controller for model has been presented. The planning a path to a target for the underwater robot has been presented using combination of optimization algorithm with learning automata and the krill herd optimization algorithm. In other words, the study has applied hybrid algorithm in order to find optimal path for the underwater robot to move in a static environment which is expressed through the map with the nodes and links
Keywords: optimization, underwater robot, state-space model, LQR optimal controller, learning automata, krill herd algorithm.
Type of Study: Research |
Subject:
Artificial Intelligence
Received: 2019/12/22 | Revised: 2020/03/3 | Accepted: 2020/03/25 | Published: 2020/04/1
Received: 2019/12/22 | Revised: 2020/03/3 | Accepted: 2020/03/25 | Published: 2020/04/1
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