Human-agent teaming for robot management in multitasking environments

In the current experiment, we simulated a multitasking environment and evaluated the effects of an intelligent agent, RoboLeader, on the performance of human operators who had the responsibility of managing the plans/routes for three vehicles (their own manned ground vehicle, an aerial robotic vehicle, and a ground robotic vehicle) while maintaining proper awareness of their immediate environment (i.e., threat detection). Results showed that RoboLeader's level of autonomy had a significant impact on participants' concurrent target detection task. Participants detected more targets in the Semi-Auto and Full-Auto conditions than in the Manual condition. Participants reported significantly higher workload in the Manual condition than in the two RoboLeader conditions (Semi-Auto and Full-Auto). Operator spatial ability also had a significant impact on target detection and situation awareness performance measures.