Performance metrics for human-robot interaction in urban search and rescue (USAR) are just beginning to appear in the literature as researchers try to establish a way of describing and evaluating human-robot task performance in this high-risk, time-critical domain. In this paper we propose that human-robot interaction metrics should focus on the work system as a whole, examining the robot's effects on human task performance within the over-arching context of human work. Moreover, these effects should be examined within the context of real-time human performance in field settings, rather than in simulation or experimental environments. This position stems from a basic assumption that we are interested in measuring human-robot interaction in USAR because we want to see how it affects and aids human performance in this time and safety-critical environment. We present a methodology for collecting data in the field and subsequent analysis using the Robot-Assisted Search and Rescue Coding System (RASAR-CS), specifically developed for this domain. The RASAR-CS allows us to capture (1) basic verbal and non verbal communications describing the task and how it is accomplished (what is being said, by who to whom); (2) situation awareness information requirements (from the robot and other sources) - for developing and maintaining situation awareness, including the ability to capture changing requirements over time; (3) team processes enabling coordinated activities, efficient communication and strategy planning; and (4) human-robot interaction in terms of: robot-operator initiated robot activities, and physical interaction with robot.
Task Performance Metrics in Human-Robot Interaction: Taking a Systems Approach
2004
8 pages
Report
No indication
English
Robotics/Robots , Computers, Control & Information Theory , Bionics & Artificial Intelligence , Robots , Systems approach , Interactions , Metrics , Field tests , Data acquisition , Search and rescue , Workshops , Urban areas , Rescue equipment , Situational awareness , Performance(Human) , Real time , Methodology , Test and evaluation , Measurement , Human-robot interaction , Performance metrics , Field methodologies
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