Body motion improves control of drone swarms but needs more effort
Body-Motion Control of a Simulated Aerial Swarm from a First-Person View
Robotics
Summary
Controlling a group of flying drones from a first-person view is tricky because you need to move the whole group carefully while keeping track of where you're looking and how spaced out the drones are. The authors made a control system that uses a person’s upper body movements, like leaning their torso and moving their hands, to guide a simulated swarm of 15 drones. People using this body-motion control finished drone navigation tasks faster and took more direct paths than using a standard controller, but they felt it required more physical effort. The study shows that this new way of controlling drone swarms can be more efficient but might tire users more.
What this means in practice
- •For drone operators: Operate drone swarms in complex environments more efficiently using body-motion controls calibrated to users.
- •For virtual reality interface designers: Design upper-body motion interfaces for controlling multiple agents in simulated 3D spaces from a first-person perspective.
Authors
Yang Chen, Darius Giannoli, Dario Floreano
Abstract
First-person-view (FPV) teleoperation of aerial swarms requires an operator to coordinate collective translation, viewing direction, and formation spacing. We present an upper-body interface that maps torso inclination, hand position, and head rotation to five continuous command dimensions. Neutral postures and motion ranges are calibrated for each participant. In a within-subject study, 14 participants navigated a simulated 15-agent swarm through three-dimensional obstacle courses using this interface and a conventional transmitter. Body-motion control reduced completion time by 19.4% and centroid path length by 7.0%, and increased path directness. Delivered-command variation was 88.8% lower, and concurrent command changes were more frequent. These command measures characterize the complete interfaces, which differed in calibration and filtering. No differences were detected in gate-centering error, collection yield, crash or disconnection counts, overall workload, or usability. All participants reported higher physical demand with body-motion control. The implemented interface therefore improved FPV navigation efficiency at the cost of greater physical demand.