Maximizing Energy Battery Efficiency in Swarm Robotics
This addresses energy management for swarm robotics in applications like object collection, though it is incremental as it builds on existing methods.
The paper tackles inefficient energy allocation in swarm robotics by introducing dynamic battery thresholds, which minimize overall energy cost and maximize performance in object gathering tasks.
Miniaturization and cost, two of the main attractive factors of swarm robotics, have motivated its use as a solution in object collecting tasks, search & rescue missions, and other applications. However, in the current literature only a few papers consider energy allocation efficiency within a swarm. Generally, robots recharge to their maximum level every time unconditionally, and do not incorporate estimates of the energy needed for their next task. In this paper we present an energy efficiency maximization method that minimizes the overall energy cost within a swarm while simultaneously maximizing swarm performance on an object gathering task. The method utilizes dynamic thresholds for upper and lower battery limits. This method has also shown to improve the efficiency of existing energy management methods.