Navigating With a Defensive Agent: Role Switching for Human Automation Collaboration

Safely navigating environments with obstacles that move stochastically cannot be guaranteed by automation, due to the motion planning becoming computationally intractable. One way to improve safety is to add a defensive escort agent that can clear paths by interacting with obstacles. When such systems also involve human-automation collaboration in the form of shared control, the addition of a defensive escort agent raises the questions about how humans interact with multiple agents with different roles. Here, we consider the human's role in a defensive escort problem where they can decide when and how to share control with the either primary or defensive agent. We implement this study within a mobile study platform designed for the investigation of different control schemes in a navigation and collision-avoidance task. We present a pilot study to demonstrate the potential for insight into this particular problem, and we find not only do humans perform better when controlling the defender than the payload, but they also actively choose to control the defender when given the choice.