An Examination of Navigation Methods for Large Immersive Virtual Environments with Application to the Study of Human-Robot Teams

Abstract

Immersive virtual environment (IVE) systems have applications in many areas, such as training, physical therapy, and entertainment. This thesis examines a fundamental function in IVEs: navigation. We built and optimized a locomotion system that allows free exploration in large IVEs within a limited physically tracked space while maintaining users’ spatial orientation. We additionally examined bipedal locomotion systems versus non-locomotive interfaces as means of moving and navigating in an IVE to determine the costs and benefits of both. This thesis then focused on an application: human-robot teaming scenarios involving locomotion and navigation. In particular, we examined how a human supervisor, in a search task, attends to robot teams, potentially large and/or geographically distributed. We examined how the presence of moving robots and an individual difference of navigation strategy affected people’s navigation ability when they were embedded with a large robot team. Our results advance cognitive findings in spatial attention division and spatial navigation of demanding scenarios. Our research may also provide important implications for the design of human-robot teams, and the command and control strategy of such teams.