An Evaluation Framework of Human-Robot Teaming for Navigation Among Movable Obstacles via Virtual Reality-Based Interactions

摘要

Robots are essential for tasks that are hazardous or beyond human capabilities. However, the results of the Defense Advanced Research Projects Agency (DARPA) Subterranean (SubT) Challenge revealed that despite various techniques for robot autonomy, human input is still required in some complex situations. Moreover, heterogeneous multirobot teams are often necessary. To manage these teams, effective user interfaces to support humans are required. Accordingly, we present a framework that enables intuitive oversight of a robot team through immersive virtual reality (VR) visualizations. The framework simplifies the management of complex navigation among movable obstacles (NAMO) tasks, such as search-and-rescue tasks. Specifically, the framework integrates a simulation of the environment with robot sensor data in VR to facilitate operator navigation, enhance robot positioning, and greatly improve operator situational awareness. The framework can also boost mission efficiency by seamlessly incorporating autonomous navigation algorithms, including NAMO algorithms, to reduce detours and operator workload. The framework is effective for operating in both simulated and real scenarios and is thus ideal for training or evaluating autonomous navigation algorithms. To validate the framework, we conducted user studies ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N = 53$</tex-math></inline-formula> ) on the basis of the DARPA SubT Challenge's search-and-rescue missions.