Search and rescueSearch-and-rescue robot operators get better with practice

Published 9 May 2011

Urban search and rescue (USAR) task forces are essential for locating, stabilizing, and extricating people who become trapped in confined spaces following a catastrophic event; sometimes the search area is too unstable for a live rescue team, so rescuers have turned to robots carrying video cameras; trouble is, research shows that more often than not, the human beings who remotely operate the robots have a view of their robot-control skills which is at variance with reality, causing robots to get stuck

Urban search and rescue (USAR) task forces are essential for locating, stabilizing, and extricating people who become trapped in confined spaces following a catastrophic event.

Sometimes the search area is too unstable for a live rescue team, so rescuers have turned to robots carrying video cameras. Most recently, the USAR robots have been employed by rescuers following the devastating Japanese earthquake and tsunami. Eurekalert, citing a Human Factors and Ergonomics Society (HFES) release, reports that the rescuers control, or teleoperate, from a safe location. Teleoperation can be problematic, as robots frequently become stuck, which can destabilize the search area and hinder rescue operations.

“The World Trade Center site was the first major real-world evaluation of robots as tools for USAR,” says Keith Jones, a researchers at HFES at Texas Tech University. “Overall, the robots performed well. One problem that did surface, however, was that the robots got stuck, a lot.” Jones, with coauthors Brian Johnson and Elizabeth Schmidlin, published a study of USAR robot teleoperation in a special issue of the Journal of Cognitive Engineering and Decision Making on human-robot interaction.

During several experiments, Jones and colleagues asked participants to drive a USAR robot through the openings of various structures. Successful navigation through openings depended on the size of the robot and the operator’s level of driving skill. Results indicated that, surprisingly, untrained operators could accurately judge the robot’s size relative to the opening. Operators, however, perceived their skill at guiding the USAR robot through the opening as greater than their performance demonstrated. This judgment factors in the size of the robot, the operator’s driving skill, and the size of the aperture. Jones and his collegues did find that, with practice, participants improved their driveability judgments.

“Our research seeks to understand why operators are getting their robots stuck,” says Jones. “With that knowledge, hopefully, we can reduce the problem, and increase the amount of time that operators spend searching for survivors.”

— Read more in Keith S. Jones, Brian R. Johnson, and Elizabeth A. Schmidlin, “Teleoperation Through Apertures: Passability Versus Driveability,” Journal of Cognitive Engineering and Decision Making 5, no. 1 (March 2011) 10–28 (DOI 10.1177/1555343411399074)