Analysis of natural gestures for controlling robot teams on multi-touch tabletop surfaces

Abstract

Multi-touch technologies hold much promise for the command and control of mobile robot teams. To improve the ease of learning and usability of these interfaces, we conducted an experiment to determine the gestures that people would naturally use, rather than the gestures they would be instructed to use in a pre-designed system. A set of 26 tasks with differing control needs were presented sequentially on a DiamondTouch to 31 participants. We found that the task of controlling robots exposed unique gesture sets and considerations not previously observed, particularly in desktop-like applications. In this paper, we present the details of these findings, a taxonomy of the gesture set, and guidelines for designing gesture sets for robot control.