Paper Info
Title
Exploratory path planning for mobile robots in dynamic environments with ant colony optimization
Abstract
ABSTRACTIn the path planning task for autonomous mobile robots, robots should be able to plan their trajectory to leave the start position and reach the goal, safely. There are several path planning approaches for mobile robots in the literature. Ant Colony Optimization algorithms have been investigated for this problem, giving promising results. In this paper, we propose the Max-Min Ant System for Dynamic Path Planning algorithm for the exploratory path planning task for autonomous mobile robots based on topological maps. A topological map is an environment representation whose focus is the main reference points of the environment and their connections. Based on this representation, the path can be composed by a sequence of state/actions pairs, which facilitates the navigability of the path, with no need to have the information of the complete map. The proposed algorithm was evaluated in static and dynamic environments, showing promising results in both of them. Experiments in dynamic environments show the adaptability of our proposal.
Year
DOI
Venue
2020
10.1145/3377930.3390219
Genetic and Evolutionary Computation Conference
Keywords
DocType
Citations 
path planning, exploration, ant colony optimization, mobile robots
Conference
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Valéria de Carvalho Santos121.07
Fernando E. B. Otero230621.29
Colin G. Johnson3933115.57
Fernando S. Osório4485.92
Cláudio F. M. Toledo500.34