Distributed Multi-Agent Systems for a Collective Construction Task based on Virtual Swarm Intelligence

In this paper, a virtual swarm intelligence VSI-based algorithm is proposed to coordinate a distributed multi-robot system for a collective construction task. Three phases are involved in a construction task: search, detect, and carry. Initially, robots are randomly located within a bounded area and start random search for building blocks. Once the building blocks are detected, agents need to share the information with their local neighbors. A distributed virtual pheromone-trail DVP based model is proposed for local communication among agents. If multiple building blocks are detected in a local area, agents need to make decisions on which agents should carry which blocks. To this end, a virtual particle swarm optimization V-PSO-based model is developed for multi-agent behavior coordination. Furthermore, a quorum sensing QS-based model is employed to balance the tradeoff between exploitation and exploration, so that an optimal overall performance can be achieved. Extensive simulation results on a collective construction task have demonstrated the efficiency and robustness of the proposed VSI-based framework.

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