Exploratory path planning for mobile robots in dynamic environments with ant colony optimization
| Autor: | Valeria de Carvalho Santos, Fernando E. B. Otero, Fernando Santos Osório, Colin G. Johnson, Claudio Fabiano Motta Toledo |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Ant colony optimization algorithms Mobile robot 0102 computer and information sciences 02 engineering and technology 01 natural sciences Task (project management) 010201 computation theory & mathematics Path (graph theory) 0202 electrical engineering electronic engineering information engineering Trajectory Robot 020201 artificial intelligence & image processing Q335 Topological map Motion planning Artificial intelligence business |
| Zdroj: | GECCO |
| DOI: | 10.1145/3377930.3390219 |
| Popis: | In 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 envi- ronments, showing promising results in both of them. Experiments in dynamic environments show the adaptability of our proposal. |
| Databáze: | OpenAIRE |
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