Task Performance Metrics in Human-Robot Interaction: Taking a Systems Approach

摘要

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 overarching 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.