Measuring Performance in Real Time during Remote Human-Robot Operations with Adjustable Autonomy

Abstract

Future NASA missions will utilize interactive robots for space exploration. Earth-based operators will remotely supervise multiple robots performing planned tasks, independently and jointly. An important aspect of such operations is the flexible allocation of tasks between the robots and their human operators, called adjustable autonomy. Metrics are needed to evaluate the effectiveness and efficiency of such operations that allocate tasks among both humans and robots. This article defines new performance metrics for such adjustable autonomy operations and presents the results of applying these metrics during a recent NASA lunar mission simulation.