Ant-Based Multi-Robot Exploration in Non-Convex Space without Global-Connectivity Constraints
Gustavo A. Cardona, David Yanguas-Rojas, Miguel F. Arevalo‐Castiblanco, Eduardo Mojica‐Nava
- 发表年份
- 2019
- 引用次数
- 13
摘要
This paper introduces an ant's behavior based exploration algorithm for multiple agents to explore non-convex environments without requiring connectivity maintenance for each instant of time. The employed algorithm emulates the pheromone trails that the real ants employ in order to avoid exploration already done by a group of robots using periodically deployed markers. Also, it includes the possibility that when two or more agents enter within their communication range, they exchange information related to the known map and the markers found. Those behaviors are integrated with a frontier based exploration algorithm, that originally required the connectivity of the network for it to work, removing this requirement and allowing it to work in broader environments.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002