OTHER
Multi mobile robot path planning based on genetic algorithm
Shuhua Liu, Yantao Tian, Jinfang Liu
- Year
- 2004
- Citations
- 26
Abstract
Genetic Algorithm has implicit parallelism and global optimization, however its computation speed constrains its on-line application. This paper attempts to apply improved genetic algorithm to multi mobile robot path planning. By using based-knowledge genetic operators, the performance of genetic algorithm is improved greatly. Simulation results showed that the improved genetic algorithm can satisfy real-time demand. In the future, it is used on-line to replan the multi mobile robot path.
Keywords
Computer scienceGenetic algorithmMotion planningMobile robotPath (computing)ComputationRobotGenetic representationCultural algorithmParallelism (grammar)
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
Open access📊 20,501 cites
Fractional Differential Equations
Igor Podlubný
2025
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991