CHS: Small: Wearable Interfaces to Direct Agent Teams with Adaptive Autonomy

New Mexico State University, Las Cruces NM

Investigators

Abstract

Unmanned robotic systems are set to revolutionize a number of vital human activities, including disaster response, public safety, citizen science, and agriculture, yet such systems are complex and require multiple pilots. As algorithms take over, and controls are simplified, workers benefit from directing, rather than controlling, these systems. Such simplifications could enable workers to use their hands and focus their perception in the physical world, relying on wearable interfaces (e.g., chording keyboards, gesture inputs) to manage teams of unmanned vehicles. Adaptive autonomy, in which unmanned systems alter their need for human attention in response to complexities in the environment, offers a solution in which workers can use minimal input to enact change. The present research combines wearable interfaces with adaptive autonomy to direct teams of software agents, which simulate unmanned robotic systems. The outcomes will support next-generation unmanned robotic system interfaces. The objective of this project is to develop wearable interfaces for the direction of a team of software agents that make use of adaptive autonomy and ascertain the effectiveness of interface designs to direct agents. This research develops a testbed for wearable cyber-human system designs that uses software agents as unmanned robotic system simulations and uses adaptive-autonomy algorithms to drive the agents. The research develops a framework connecting wearable interface modalities to the activities they best support. Developed systems will be validated through mixed reality environments in which participants will direct software agents while acting in the physical world. The principal hypothesis is that a set of interconnected interfaces can be developed that, through appropriate control algorithms, maximizes an operator's control span over a team of agents and optimizes the operator's physical workload, mental workload, and situation awareness.