Human Interaction Through an Optimal Sequencer to Control Robotic Swarms

Abstract

The interaction between swarm robots and human operators is significantly different from the traditional humanrobot interaction due to unique characteristics of the system, such as high cognitive complexity and difficulties in state estimation. In this paper, we concentrate on a method for conveying input from the operator to the swarm. Previous research has shown that control through switching between behaviors offers the greatest flexibility but is particularly difficult for human operators. A recently developed method for finding optimal sequences for composing behaviors offers a potential tool for aiding human operators controlling swarms through behavior switching. This paper compares participants performing a navigation task with and without the availability of an optimal sequencing aid. Results show that the task of preplanning a sequence of behaviors and durations is more difficult for participants than switching between executing behaviors to navigate. Users who used the aid frequently created shorter paths than infrequent users and the control group. In the trials that the aid was used, participants tended to generate more complicated sequences and achieve the first attempt more rapidly, than trials in which the aid was not used.