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An energy-aware collaborative multi-agent system for autonomous underwater vehicles

Underwater vehicles most of the time operate in environments that normally are inaccessible to humans. They can operate in the depth of the ocean where they have challenging conditions such as: pressure, light and visibility, among others. Collaborative autonomous underwater vehicle (AUV) systems provide a possibility to create groups to work as a team and do some specific tasks that generally cannot be done by only one vehicle, saving time and energy in the network. Collaborative approaches aim to improve the response time of the task and save the energy on the network. This paper compares the efficacy and efficiency of three different approaches that use multi-agent systems. All approaches use different zones or clusters of vehicles. The first approach uses a leader AUV responsible for the message propagation, the second uses cluster heads and the third one uses a BDI model (Belief, Desire and Intention) to allow the agents to have a simple human behavior. The results show that the second and third approaches reduce the energy consumed in the network compared with the first approach (leader).