On the Design of Social Robots Using Sheaf Theory and Smart Contracts - Murimi, Renita (Frontiers in Robotics and AI, 2021)
The incorporation of robots in the social fabric of our society has taken giant leaps, enabled by advances in artificial intelligence and big data. As these robots become increasingly adept at parsing through enormous datasets and making decisions where humans fall short, a significant challenge lies in the analysis of robot behavior. Capturing interactions between robots, humans and IoT devices in traditional structures such as graphs poses challenges in the storage and analysis of large data sets in dense graphs generated by frequent activities. This paper proposes a framework that uses the blockchain for the storage of robotic interactions, and the use of sheaf theory for analysis of these interactions. Further, the use of smart contracts on the blockchain is proposed with an embedding of two parameters in the smart contracts – imperfect information and irrationality – to enable robots to operate deftly in various human environments that expect different levels of dominance from the robot. This work shows the application of such a framework for various blockchain applications on the spectrum of human-robot interaction, and identifies key challenges that arise as a result of using the blockchain for robotic applications.