Virtual Shadow Rendering for Maintaining Situation Awareness in Proximal Human-Robot Teaming

Andrew Boateng, Yu Zhang

Keywords: Augmented Reality, Virtual Shadow, Human Robot Interaction

TL;DR: Persistent visual rendering of robot position at all time

Abstract:

One focus of augmented reality (AR) in robotics has been on enriching the interface for human-robot interaction. While such an interface is often made intuitive to interact with, it invariably imposes novel objects into the environment. In situations where the human already has a focus, such as in a human-robot teaming task, these objects can potentially overload our senses and lead to degraded teaming performance. In this paper, we propose using AR objects to solely augment natural objects to avoid disrupting our natural senses while adding critical information about the current situation. In particular, our case study focuses on addressing the limited field of view of humans by incorporating persistent virtual shadows of robots for maintaining situation awareness in proximal human-robot teaming tasks.
We designed a novel process to generate such shadows and verified that they worked better than other commonly adopted methodologies in teaming scenarios.

Track: extended abstract

Broader Impacts:

There have been instances where robots have caused significant injuries to humans. This is mainly due to the fact that the human did not know of the robot’s current activity, position, or trajectory. Having robot information at all times is therefore a good safety measure.
Persistent virtual Shadow rendering is also good for search and rescue operations. At places where there is no good lighting or too dangerous for humans, rescuers will be able to know their deployed robot counterpart’s activities and the location at all times from shadow activities.
Shadows also give a “real” look/feeling to virtually rendered robots. In general, it makes the AR experience a better one