A Networking Framework for Multi-Robot Coordination

Autonomous robots operating in real environments need to be able to interact with a dynamic world populated with objects, people, and, in general, other agents. The current generation of autonomous robots, such as the ASIMO robot by Honda or the QRIO by Sony, has showed impressive performances in mechanics and control of movements; moreover, recent literature reports encouraging results about the capability of such robots of representing themselves with respect to a dynamic external world, of planning future actions and of evaluating resulting situations in order to make new plans. However, when multiple robots are supposed to operate together, coordination and communication issues arise; while noteworthy results have been achieved with respect to the control of a single robot, novel issues arise when the actions of a robot influence another's behavior. The increase in computational power available to systems nowadays makes it feasible, and even convenient, to organize them into a single distributed computing environment in order to exploit the synergy among different entities. This is especially true for robot teams, where cooperation is supposed to be the most natural scheme of operation, especially when robots are required to operate in highly constrained scenarios, such as inhospitable sites, remote sites, or indoor environments where strict constraints on intrusiveness must be respected. In this case, computations will be inherently network-centric, and to solve the need for communication inside robot collectives, an efficient network infrastructure must be put into place; once a proper communication channel is established, multiple robots may benefit from the interaction with each other in order to achieve a common goal. The framework presented in this paper adopts a composite networking architecture, in which a hybrid wireless network, composed by commonly available WiFi devices, and the more recently developed wireless sensor networks, operates as a whole in order both to provide a communication backbone for the robots and to extract useful information from the environment. The ad-hoc WiFi backbone allows robots to exchange coordination information among themselves, while also carrying data measurements collected from surrounding environment, and useful for localization or mere data gathering purposes.