Largest Indoor Mocap Facility in Academia Provides For World Leading Drone Research

With a tracking volume of 230,000 cubic feet, Arizona State University’s Drone Studio is the largest indoor mocap facility for drone research at any academic institution in the world. Formerly a basketball gym, the facility was more than five years in the making and was envisioned by ASU robotics researcher and Associate Professor Panagiotis Artemiadis, Ph.D., as a collaborative space for interdisciplinary research.

With 23-foot-tall ceilings, and 104 wide-angle OptiTrack Prime 17W cameras, Drone Studio’s tracking system is capable of capturing 360 measurements per second for up to 250 robots simultaneously, with each drone’s movement tracked within 0.5 millimeter accuracy, making the space aptly suited for studying drone swarms, fast dynamics and large platform robots. Dr. Artemiadis, who made waves in 2016 with his innovative brain activity-driven drone control system research at ASU’s Human-Oriented Robotics and Control (HORC) Lab, leads Drone Studio along with Stephanie Gil, an assistant professor in ASU’s School of Computing, Informatics, and Decision Systems Engineering.

In addition to supporting the study and development of aerial robotics systems, Drone Studio also accommodates ground robots, allowing researchers to examine and coordinate interactions between robots with varied means of locomotion. The real-world implications of such studies can aid in the development of emerging technologies such as unmanned search and rescue vehicles, autonomous vehicles, and drone deliveries.

Describing Drone Studio to Convergence, ASU’s Fulton Schools of Engineering Magazine, Dr. Artemiadis said, “This state-of-the-art instrumented space allows multi-disciplinary teams of faculty to address research questions and problems that could not be addressed before, such as coordination and control of hundreds of robotic agents and human-swarm interaction among others.”

Gil noted, “I want the Drone Studio to inspire researchers to attempt new classes of experiments that capitalize on the combination of working in a large space with real-time tracking capabilities, to reveal novel understandings of how best to coordinate, control and model large robot systems.”