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文章基本信息

  • 标题:Artificial Intelligence in Robot Path Planning
  • 本地全文:下载
  • 作者:Yogita Gigras ; Kusum Gupta
  • 期刊名称:International Journal of Soft Computing & Engineering
  • 电子版ISSN:2231-2307
  • 出版年度:2012
  • 卷号:2
  • 期号:2
  • 页码:471-474
  • 出版社:International Journal of Soft Computing & Engineering
  • 摘要:Mobile robot path planning problem is an important combinational content of artificial intelligence and robotics. Its mission is to be independently movement from the starting point to the target point make robots in their work environment while satisfying certain constraints. Constraint conditions are as follows: not a collision with known and unknown obstacles, as far as possible away from the obstacle, sports the shortest path, the shortest time, robot-consuming energy minimization and so on. In essence, the mobile robot path planning problem can be seen as a conditional constraint optimization problem. To overcome this problem, ant colony optimization algorithm is used.
  • 关键词:Particle Swarm Optimization (PSO); Genetic;Algorithm(GA); Tabu Search; Simulated Annealing (SA);Reactive;Search;Optimization;(RSO);proportional–integral–derivative(PID).
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