Trust Management Framework for Multi-Robot Systems

As autonomous technologies blend into a variety of industries, the employment of Multi-Robot Systems (MRS) in complex tasks is becoming increasingly prevalent. These systems, characterized by their distributed intelligence and collaborative capabilities, are now largely deployed in executing critical missions ranging from environmental exploration to disaster response. To support the trustworthy execution of such collaborative multi-robot missions, the existence of an underlying trust management framework is becoming imperative, given the rising risks of malicious intruders attempting to join the MRS. This paper proposes a Trust Management Framework (TMF) for Multi-Robot Systems, to bridge the gap of scarce trust management support for MRS. By analyzing trust dynamics and integrating direct and indirect trust with contextual data, we address the trust vulnerabilities inherent to MRS. Our primary contribution is the development of a novel TMF significantly supporting the trust, security and reliability of MRS. The paper systematically outlines the evolution of our TMF, from theoretical underpinnings to an integrated solution, and the discussion of its impact on the trustworthiness of cooperative robotic networks.