Vision based Virtual Guidance for Navigation

This paper explores the impact of virtual guidance on mid-level representation-based navigation, where an agent performs navigation tasks based solely on visual observations. Instead of providing distance measures or numerical directions to guide the agent, which may be difficult for it to interpret visually, the paper investigates the potential of different forms of virtual guidance schemes on navigation performance. Three schemes of virtual guidance signals are explored: virtual navigation path, virtual waypoints, and a combination of both. The experiments were conducted using a virtual city built with the Unity engine to train the agents while avoiding obstacles. The results show that virtual guidance provides the agent with more meaningful navigation information and achieves better performance in terms of path completion rates and navigation efficiency. In addition, a set of analyses were provided to investigate the failure cases and the navigated trajectories, and a pilot study was conducted for the real-world scenarios.