Decision-theoretic human-robot communication

Abstract

Humans and robots need to exchange information if the objective is to achieve a task cooperatively. Two questions are considered in this paper: what type of information to communicate, and how to cope with the limited resources of human operators. Decision-theoretic human-robot communication can provide answers to both questions: the type of information is determined by the underlying probabilistic representation, and value-of-information theory helps decide when it is appropriate to query operators for information. A robot navigation task is used to evaluate the system by comparing it to conventional teleoperation. The results of a user study show that the developed system is superior with respect to performance, operator workload, and usability.

Using mixed-initiative human-robot interaction to bound performance in a search task

“…Other efforts in mixed-initiative solutions include Kaupp and Makarenko where the robot queries the human operator when the robot decides the human's information is worthwhile [12]. Their work was evaluated in simulation with plans to extend to a physical system.…”

Field trial for simultaneous teleoperation of mobile social robots

“…Kaupp et al have also recently done research in this direction [15], using robot-initiated notifications of error states to reduce teleoperation workload for navigational tasks.…”

Designing interfaces for multi-user, multi-robot systems

“…There is also a mature body of work on how to create a salient display, manage awareness, and command attention [1,7,11,13,15,16,25,32,36]. However, what operators want their attention directed towards and how this need changes with respect to operator role and context is unaddressed.…”