Exploration and map-building under uncertainty with multiple heterogeneous robots

In this paper, we present a multi-robot exploration strategy for map-building. We consider a team of robots with different sensing and motion capabilities. We combine geometric and probabilistic reasoning to propose a solution to our problem. We formalize the proposed solution using dynamic programming in states with imperfect information. We apply the dynamic programming technique in a reduced search space that allows us to incrementally explore the environment. We propose realistic sensor models and provide a method to compute the probability of the next sensor reading given the current state of the team of robots based on a Bayesian approach.