A Multi-Robot Architecture Framework for Effective Robot Teammates in Mixed-Initiative Teams

Abstract

Effective robotic teammates should be able to interact with humans in natural language about all task aspects, keep track of task and team states to coordinate their actions, and handle unexpected events autonomously. In this paper, we introduce a multi-robot architectural framework for effective robot teammates that allows robots to learn new tasks on the fly and monitor task execution to be able to detect unexpected faults and events. It enables robots to generate recovery plans, assess their effectiveness, and engage with human teammates in problem solving dialogues. We demonstrate the capabilities and operation of the framework in a complex mixed-initiative human-robot medical assembly and delivery task.