Cornering Law

Abstract

Objective: We investigated skill development and workload of pilots driving teleoperated unmanned ground vehicles (UGVs) through different apertures and viewpoints using the cornering law. Background: Due to technological and cost restraints, humans are still needed for tasks involving UGVs. Operators of teleoperated UGVs are likely to have less situation awareness and thus are more prone to getting stuck or damaged when negotiating apertures. To our knowledge, the operation of physical UGVs through corners has not been examined. Therefore, a better understanding of cornering a teleoperated UGVs is imperative. Method: In Experiment 1, 20 novice participants repeatedly teleoperated a physical UGV using a third-person overhead view through apertures that varied in width. In Experiment 2, 18 additional novice participants completed a similar task but used a first-person view. Results: Participants’ performance increased (i.e., faster cornering times and less collisions) over sessions. The cornering law successfully modeled the effect of different aperture widths on participant performance for both viewing perspectives. Conclusion: In this study, we successfully modeled human performance of teleoperated UGVs using the cornering law. Analogous to Fitts’ and steering law, we were able to successfully model and predict cornering performance based on a derived index of cornering difficulty. Application: The cornering law could be used to aid in the development of prototype user interfaces and also to examine the effects of different teleoperation views (first person vs. third person).