An extremal fields approach for the analysis of human planning and control performance

In this paper we describe a study of the human pilot control behavior in a planar goal directed flight task. The experimental data was collected using a miniature helicopter in an indoor flight test facility. To provide insight into the human´s control behavior we developed a technique to extract extremal fields from the family of collected trajectories. These fields describe the spatial distribution of the vehicle states and cost- to-go, including their statistical distribution, which provides information about the variability of the pilot´s control behavior over the task domain. Once extracted we can compare these fields to the value functions obtained from the task´s equivalent optimal control problem. The comparison of the human-extracted and the computed value function maps suggests that on average, the human acts similarity to an optimal control policy. The results also suggests that a simple mass-point model used for our analysis, and motivated by the hypothesis that the pilot acts as a dynamic inverse controller, is sufficient to explain the pilot´s performance at the planning level. We use these results to develop hypotheses about human planning and control processes and discuss their biological plausibility based on control-theoretic interpretations. We plan to use the new insights from this framework to help design more capable and versatile algorithms for autonomous vehicle control, as well as help design man-machine interfaces that enable a more natural link with the operator´s internal control and planning processes.