David Stager is a Senior Commercialization Specialist for the National Robotics Engineering Center (NREC). His interests are in unmanned vehicle design, computer vision, machine learning, medical robotics, and complex autonomous systems.
As lead engineer for the Crusher unmanned ground vehicle (UGV), he led the development of power distribution, engine, brakes, suspension, computing, perception, and other vehicle subsystems. He also supervised several years of field testing activities. Prior to this project, he led electronics and software development for the hybrid-electric Spinner UGV. He served as lead integrator for the Robotics Vehicle Control Architecture (RVCA) project, which used one of the Crusher vehicles to implement Future Combat Systems software. On CargoUGV, David created much of the infrastructure and perception system which enables convoy vehicles to drive autonomously for the marines.
Computer Vision / Machine Learning:
His machine vision work includes designing and implementing a computer vision system to inspect coal mine conveyor belts. This system is in use in several active mines and saves hundreds of thousands of dollars yearly in unscheduled belt downtime. He also designed and implemented a computer vision library to classify and sort images of strawberry plants which is being patented and is now licensed by the majority of strawberry nurseries in the United States.
David is the lead systems engineer on the Darpa Robotics Challenge team ‘Tartan Rescue’, creating one of the world’s most advanced humanoid robots. David helps lead NREC’s core technology being used across multiple programs. He has also been working on business development in the medical robotics field, applying NREC’s capabilities in exciting new areas.
Stager holds a BS in Electrical and Computer Engineering / Math and Computer Science (double major) from Carnegie Mellon University (1995) and a MS in Robotics from Carnegie Mellon University (2007). He has published several papers and holds a United States patent for the conveyor belt inspection system. He also received the DARPA Research Excellence Award and the Allen Newell Research Excellence award.
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