Loading...

Efficient and safe path planning for a mobile robot using genetic algorithm

Naderan Tahan, M ; Sharif University of Technology | 2009

315 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/CEC.2009.4983199
  3. Publisher: 2009
  4. Abstract:
  5. In this paper, a new method for path planning is proposed using a genetic algorithm (GA). Our method has two key advantages over existing GA methods. The first is a novel environment representation which allows a more efficient method for obstacles dilation in comparison to current cell based approaches that have a tradeoff between speed and accuracy. The second is the strategy we use to generate the initial population in order to speed up the convergence rate which is completely novel. Simulation results show that our method can find a near optimal path faster than computational geometry approaches and with more accuracy in smaller number of generations than GA methods. © 2009 IEEE
  6. Keywords:
  7. Genetic algorithm ; CBPRM ; Computation geometry ; Convergence rates ; Current cells ; Efficient method ; Initial population ; Optimal paths ; Path-planning ; Safe path planning ; Simulation result ; Speed-ups ; Computational efficiency ; Computational geometry ; Genetic algorithms ; Mobile robots ; Motion planning ; Navigation ; Robot programming
  8. Source: 2009 IEEE Congress on Evolutionary Computation, CEC 2009, Trondheim, 18 May 2009 through 21 May 2009 ; 2009 , Pages 2091-2097 ; 9781424429592 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4983199?arnumber=4983199&tag=1