LEARNING
Path planning method for mobile robot based on ant colony optimization algorithm
Yuwan Cen, Choingzhi Song, Nenggang Xie, Lu Wang
- Year
- 2008
- Citations
- 18
Abstract
A novel path planning approach based on ACO was presented aiming at mobile robots in structured environments. The information of environment constrains and path length was integrated in the fitness function which was computed by neural network, the path nodes were viewed as an ant, so with the quality of optimization of ant colony optimization algorithm, the best path was found. Finally by computer simulation, it is got that the algorithm is rational and can be used in process industry warehouse patrol measurement mobile robot real-time navigation.
Keywords
Ant colony optimization algorithmsMotion planningMobile robotComputer sciencePath (computing)Fitness functionArtificial neural networkRobotProcess (computing)Ant colony
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 cites
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002