Building Volumetric Maps with Cooperative Mobile Robots and Useful Information Sharing: a Distributed Control Approach based on Entropy

This thesis addresses the problem of how to share efficiently information within a robotic system comprised of several mobile robots, which are programmed to exhibit cooperative behavior in the context of building volumetric maps of unknown environments. More specifically, it addresses the following issues: representing a probabilistic map and improving it through efficient exploration, based on information gain maximization; distributed control of teams of cooperative mobile robots, based on an information utility criteria; and coordinated exploration, aiming at avoiding redundant sensory information and robots’ interference. Robots have been developed essentially to help or substitute humans in tasks which are either repetitive or dangerous. For many of these tasks, especially those that are intrinsically distributed and complex, a team of several cooperative mobile robots — a cooperative multi-robot system (MRS) — is required to either make viable the mission accomplishment or, at least, accomplish the mission with better performance than a single mobile robot. In spite of potential advantages related with space distribution, time distribution, complex problems decomposition, robustness, reliability and cost, a MRS requires that each robot maintains a sufficient and consistent level of awareness about the mission assigned to the team and about its teammates, in order to attain effective cooperation. The main challenge is that information is distributed and thus each robot has only partial and, sometimes, inconsistent knowledge about the environment. Sharing efficiently information via communication is thus crucial for robots’ cooperation. Building maps is indeed a relevant robotics’ application domain. Firstly, in many other