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 concentrated on the method of 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 offered a potential tool for aiding human operators controlling swarms through behavior switching. This paper compared participants performing a navigation task with and without the availability of the optimal sequencing aid. Results showed that the task of preplanning a sequence of behaviors and durations appeared more difficult for participants than switching between executing behaviors to navigate. Users who used the aid frequently was found to create shorter paths than infrequent users and the control group. In the trails that the aid was used, participants tended to generate more complicated sequences and achieve the first attempt more rapidly, compared to the trails that the aid was not used.