Task Decomposition and Multi-Robot Task Allocation in Exploration With Bayesian Networks

Although exploration methods for homogeneous multi-robot systems have improved, they generally lack consideration for the impact of robot capabilities on exploration in complex environments. To address this, we propose a task-allocation method based on Bayesian Networks for decentralized heterogeneous systems. Tasks are randomly distributed in unexplored areas, guiding robots to complete the exploration. Our method is demonstrated in real-world ground environments.