Computational Cognitive Modeling of Operator Behavior in Telerover Navigation

Abstract

The objective of this study was to demonstrate the use of a computational cognitive model for representing human performance in robotic rover control and to make comparison with actual human performance. In manual control trials, an operator was required to navigate a commercially available rover along a path using a remote workstation. A cognitively plausible GOMSL (Goals, Operators, Methods, Selection rules) model for controlling the rover was constructed based on a task analysis and observations during the human trials. Time-to-navigation completion and path tracking accuracy were recorded during the human performance and cognitive model trials with navigation conditions being identical. Model output demonstrated the GOMSL code to produce more precise control of the rover than human performance, but this was at the cost of time. This result was attributable to limitations of the modeling approach in terms of representing human parallel processing and continuous control. In general, computational GOMS modeling approaches appear to have the potential to describe interactive closed-loop system control with continuous monitoring of feedback and corresponding control actions.