William R. Michalson
Robot swarms are often considered suitable for tasks that are large-scale and long-term. Large-scale missions force the robots to spread spatially. In these type of tasks, actively maintaining connectivity allows the swarm to coordinate. Similarly, long-term nature of the task requires robots to work for a long time. This is affected by the limited energy level of the robot. However current studies normally focus only on connectivity or energy awareness. Therefore, in this work, we propose an approach to tackle the problem of maintaining global connectivity (swarm-level property) considering finite battery life (individual property). We are specifically focusing on growing the communication network and keeping it alive for a long period. We construct a logical tree over the connectivity graph. The logical tree is constructed by using a subset of robots from the swarm. The tree is grown by adding robots as necessary. The tree is also periodically reconfigured to cope with dynamic robot motion. This enables the swarm to grow the tree efficiently. In addition, robots exchange their roles based on their available energy levels. This allows robots with low energy levels to navigate to dedicated charging stations for recharging thus allowing the swarm to maintain the communication network. We evaluate our approach in a wide set of experiments with a realistic robot simulator named ARGoS.
Worcester Polytechnic Institute
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Jayabalan, Adhavan, "Decentralized Persistent Connectivity Deployment in Robot Swarms" (2018). Masters Theses (All Theses, All Years). 1231.
swarm robotics, connectivity deployment, energy awareness
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