A Novel Metric for Evaluating Human-Robot Navigation Performance Need for Metrics

Abstract

It is frequently desirable to quantitatively evaluate performance in human-robot interaction. In this research, we introduce a novel use of fractal based performance measures to evaluate robot navigation. It can be difficult to use simple measurements such as path length and task timing due to large amounts of individual variability along these metrics. This shortcoming makes these measures particularly unsuitable for evaluating human/robot navigation performance in a complex environment with multiple tasks. Herein we outline a class of novel metrics for evaluating navigation performance using fractal geometry. This class of space and time invariant metrics allows us to better analyze human-robot exploration, interpret valuable behavioral information for analysis of movement, measure the handler/robot's search efficiency, path tortuosity, and overall space utilization in relation to handler goals and overall characteristics of the environment. We present techniques for computation and empirical results from our own navigation interface studies.