A Framework for Learning by Demonstration in Multi-teacher Multi-robot Scenarios

Abstract

As robots become more accessible to humans, more intuitive and human-friendly ways of programming them with interactive and group-aware behaviours are needed. This thesis addresses the gap between Learning by Demonstration and Multi-robot systems. In particular, this thesis tackles the fundamental problem of learning multi-robot cooperative behaviour from concurrent multi-teacher demonstrations, problem which had not been addressed prior to this work. The core contribution of this thesis is the design and implementation of a novel, multi- layered framework for multi-robot learning from simultaneous demonstrations, capable of deriving control policies at two different levels of abstraction. The lower level learns models of joint-actions at trajectory level, adapting such models to new scenarios via feature mapping. The higher level extracts the structure of cooperative tasks at symbolic level, generating a sequence of robot actions composing multi-robot plans. To the best of the author's knowledge, the proposed framework is the first Learning by Demonstration system to enable multiple human demonstrators to simultaneously teach group behaviour to multiple robots learners. A series of experimental tests were conducted using real robots in a real human workspace environment. The results obtained from a comprehensive comparison confirm the appli- cability of the joint-action model adaptation method utilised. What is more, the results of several trials provide evidence that the proposed framework effectively extracts rea- sonable multi-robot plans from demonstrations. In addition, a case study of the impact of human communication when using the proposed framework was conducted, suggesting no evidence that communication affects the time to completion of a task, but may have a positive effect on the extraction multi-robot plans. Furthermore, a multifaceted user study was conducted to analyse the aspects of user workload and focus of attention, as well as to evaluate the usability of the teleoperation system, highlighting which parts were necessary to be improved.