Abstract
We propose an efficient scheme based on a swarm robotics approach for exploring unknown environments. The initial goal is to trace a map which is later used to find optimal paths. The algorithm minimizes distance and danger. The proposed scheme consists in three phases: exploration, mapping and path optimization. A cellular automata approach is used for the simulation of the fist two phases. For the exploration phase, a stigmergy approach is applied in order to allow for swarm communication in a implicit way. For the path planning phase a hybrid method is proposed. First an adapted Rapidly-exploring Random Graph algorithm is used and then a scalarized multiobjective technique is applied to find the shortest path.
Highlights
Swarm algorithms have been deeply studied to address problems such as food search and object collection
Analyzing random walk with direction (RWD) against the two pheromone methods, we can see that under certain configuration of Υ0, the performance of pheromone walk (PW) can be similar to RWD, is PWD the one that stand out (Fig. 5). Given this results we can assure that if we add direction to the movement of an agent and give him the ability to communicate its path through the environment with pheromones, the dispersion and coverage of the swarm in the area can be accomplish in a more faster and efficient way
The solution was composed by three phases: exploration, mapping and path planning, and was made under computer simulations with swarms of ten, fifteen and twenty agents
Summary
There are several swarm applications that have been studied: aggregation, flocking, exploration, foraging, navigation, path formation, object assembly and others [1], [3], [4] In many of this applications, the use of a swarm is desired given the dangerous nature of the task. In this paper we focus our work on the exploration of unknown, static and dangerous environments These tasks can be executed by humans, the use of swarm robotics will allow to save resources and protect the people in charge of those tasks. A simulated swarm based on a cellular automata scheme will be used for exploring unknown environments This scheme autonomously propitiate an efficient dispersion of the swarm through the unknown area. In the last one general conclusions of the work will be discussed
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