Simultaneous Localization and Mapping (SLAM) for Route Reversal Learning

Abstract

(1) Background: In this paper, we describe the design of a virtual environment (VE) using Simultaneous Localization and Mapping (SLAM) to scan and replicate a real environment (RE) in a virtual domain. Compared to using a CAD software, SLAM allows for the replication of an RE quite easily and quickly. (2) Methods: To test the user’s performance in a SLAM-based VE, we developed an immersive virtual reality setup using a specialized wheelchair (VRNChair) and a head mounted display (Oculus Rift DK2), and employed a knowledge transfer paradigm to investigate navigational performance differences in an RE and its replica in a VE. Our hypothesis was knowledge transfers between the VE and RE would be comparable. Sixteen male students (age of 20.2±2.7 years) learned a route in either an RE or its replica in VE, and then were required to return to the starting point in the counterpart environment. (3) Results: The textures of the environment were substantially degraded in the SLAM-based VE. However, the knowledge transfers between the VE and the RE were not significantly different. (4) Conclusions: Route-based knowledge is transferable between a SLAM-created VE and RE.