Task Versus Vehicle-Based Control Paradigms in Multiple Unmanned Vehicle Supervision by a Single Operator

Abstract

There has recently been a significant amount of activity in developing supervisory control algorithms for multiple unmanned aerial vehicle operation by a single operator. While previous work has demonstrated the favorable impacts that arise in the introduction of increasingly sophisticated autonomy algorithms, little work has performed an explicit comparison of different types of multiple unmanned vehicle control architectures on operator performance and workload. This paper compares a vehicle-based paradigm (where a single operator individually assigns tasks to unmanned assets) to a task-based paradigm (where the operator generates a task list, which is then given to the group of vehicles that determine how to best divide the tasks among themselves.) The results demonstrate significant advantages in using a task-based paradigm for both overall performance and robustness to increased workload. This effort also demonstrated that while previous video gaming experience mattered for performance, the degree of experience that demonstrated benefit was minimal. Further work should focus on designing a flexible automated system that allows operators to focus on a primary goal, but also facilitate lower level control when needed without degradation in performance.

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