We like to share your success stories. At the end of last year we asked our members to offer some case studies which they were proud of and we devoted a section of the last euRobotics Annual Report to as many of these as we could. There wasn’t space or time to include every story submitted, though, so we decided to follow up by publishing some of those extra stories here in the newsletter. In the last edition you may have read about solar farm construction using a solution from Comau. This month we reproduce a case study from Qualisys. There will be another member’s success story in the next edition, too.

Drone and Autonomous Vehicle Tracking at M-Air

M-Air is a 10,000-square-foot, four-story research facility designed to study autonomy and collaborative robotics in real Michigan weather—from freezing winters to humid summers with snow, rain, hail, and sleet. The facility uses 34 Qualisys cameras to track and analyze autonomous flight and ground vehicles outdoors, even in extreme conditions.

Located next to the new Ford Robotics Building, M-Air fosters collaboration among roboticists and is near Mcity, wind tunnels, and water tanks for comprehensive autonomous vehicle testing. The outdoor space allows experiments in realistic conditions, such as flying quadrotors in wind or testing ground robots on varied surfaces. For example, Robotics PhD candidate Ross Hartley used M-Air motion capture as ground truth to evaluate a robot’s state estimator, comparing 3D orientation, position, and velocity estimates from IMU, joint encoder, and contact sensors.

Research at M-Air focuses on resilient algorithms that ensure multi-agent systems can achieve goals even when some robots are faulty, hacked, or broken. With its large outdoor space, M-Air enables experiments that were impossible indoors, supporting complex multi-agent studies safely and reliably.Ross Hartley, Robotics PhD, University of Michigan: “The key benefit of M-Air is the large outdoor space covered by the Qualisys Motion Capture system. Indoor setups were too limited, but here we can run long experiments without losing tracking.”

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