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Optimization of dynamic mobile robot path planning based on evolutionary methods

Fetanat, M ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1109/RIOS.2015.7270743
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2015
  4. Abstract:
  5. This paper presents evolutionary methods for optimization in dynamic mobile robot path planning. In dynamic mobile path planning, the goal is to find an optimal feasible path from starting point to target point with various obstacles, as well as smoothness and safety in the proposed path. Pattern search (PS) algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to find an optimal path for mobile robots to reach to target point with obstacle avoidance. For showing the success of the proposed method, first they are applied to two different paths with a dynamic environment in obstacles. The first results show that the PSO algorithms are converged and minimizethe objective function better that the others, while PS has the lower timecompared to other algorithms in the initial and modified environment. The second test path is in the z-type environment that we compare the mentioned algorithms on it. Also in this environment, the same result is repeated. © 2015 IEEE
  6. Keywords:
  7. Evolutionary Algorithms ; Mobile Robot ; Path Planning ; Algorithms ; Artificial intelligence ; Genetic algorithms ; Motion planning ; Optimization ; Particle swarm optimization (PSO) ; Robot programming ; Robotics ; Robots ; Dynamic environments ; Evolutionary method ; Objective functions ; Optimal paths ; Pattern search ; PSO algorithms ; Robot path-planning ; Target point
  8. Source: 2015 AI and Robotics, IRANOPEN 2015 - 5th Conference on Artificial Intelligence and Robotics, 12 April 2015 ; April , 2015 , Page(s): 1 - 7 ; 9781479987337 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7270743