Guest Editorial Special Issue on Control of Very-Large-Scale Robotic (VLSR) Networks

Abstract

Future applications of autonomous systems promise to involve increasingly large numbers of collaborative robots individually equipped with onboard sensors, actuators, and wireless communications. By sharing and coordinating information, plans, and decisions, these very-large-scale robotic (VLSR) networks can dramatically improve their performance and operate over long periods of time with little or no human intervention. Controlling many collaborative agents to this day presents significant technical challenges. Besides requiring satisfactory communications, the amount of computation associated with most coordinated control algorithms increases with the number of agents. It is well-known, for example, that the optimal control of N collaborative agents for path planning and obstacle avoidance is a PSPACE-hard problem. Also, while necessary for performing basic tasks such as localization and mapping, many sensing and estimation approaches suffer from the curse of dimensionality, and their performance may degrade as uncertainties from disparate sources propagate through the network.