Indy: a virtual reality multi-player game for navigation skills training

TL;DR

Indy is a collaborative virtual reality game designed to enhance navigation skills training in complex industrial environments by enabling active, repeated, and feedback-rich learning experiences.

Contribution

This paper introduces Indy, a novel VR-based multiplayer game that improves navigation training through active engagement and repeated practice, addressing limitations of traditional methods.

Findings

Enhanced navigation skills through VR training

Increased training repetitions and duration

Active engagement improves learning outcomes

Abstract

Working in complex industrial facilities requires spatial navigation skills that people build up with time and field experience. Training sessions consisting in guided tours help discover places but they are insufficient to become intimately familiar with their layout. They imply passive learning postures, are time-limited and can be experienced only once because of organization constraints and potential interferences with ongoing activities in the buildings. To overcome these limitations and improve the acquisition of navigation skills, we developed Indy, a virtual reality system consisting in a collaborative game of treasure hunting. It has several key advantages: it focuses learners' attention on navigation tasks, implies their active engagement and provides them with feedbacks on their achievements. Virtual reality makes it possible to multiply the number and duration of situations that learners can experience to better consolidate their skills. This paper discusses the main design principles and a typical usage scenario of Indy.