Teaching Collaborative Multi-Robot Tasks through Demonstration

Humanoid robots working alongside humans in everyday environments is a long standing goal of the robotics community. To achieve this goal, methods for developing new robot behaviors that are intuitive and accessible to non-programmers are required. In this paper, we present a demonstration-based method for teaching distributed autonomous robots to coordinate their actions and perform collaborative multi-robot tasks. Within the presented framework, each robot learns an individual policy from teacher demonstrations using a confidence-based algorithm. Based on this learning approach, we contribute three techniques for teaching multi-robot coordination using different information sharing strategies. We evaluate and compare these approaches by teaching two Sony QRIO humanoid robots to perform three collaborative ball sorting tasks.