title: Cornering law: the difficulty of negotiating corners with an unmanned ground vehicle.
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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
  
  
  CONCLUSIONS
  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).
authors.forename: William S
authors.initials: WS
authors.lastname: Helton
authors.forename: James
authors.initials: J
authors.lastname: Head
authors.forename: Benno A
authors.initials: BA
authors.lastname: Blaschke
mesh_terms: D000293:Adolescent; D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D009038:Motion; D012371:Robotics; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D016526:Workload; D055815:Young Adult