Carnegie Mellon and Argo AI create autonomous vehicle research center
Carnegie Mellon University and Argo AI announced a five-year, $15 million sponsored research partnership under which the self-driving technology company will fund research into advanced perception and next-generation decision-making algorithms for autonomous vehicles.
The partners will establish the Carnegie Mellon University Argo AI Center for Autonomous Vehicle Research, which will pursue advanced research projects to help overcome hurdles to enabling self-driving vehicles to operate in a wide variety of real-world conditions, such as winter weather or construction zones.
"We are thrilled to deepen our partnership with Argo AI to shape the future of self-driving technologies," CMU President Farnam Jahanian said. "This investment allows our researchers to continue to lead at the nexus of technology and society, and to solve society's most pressing problems. Together, Argo AI and CMU will accelerate critical research in autonomous vehicles while building on the momentum of CMU's culture of innovation."
”Argo AI, Pittsburgh, and the entire autonomous vehicle industry have benefited from Carnegie Mellon’s leadership. It’s an honor to support development of the next generation of leaders and help unlock the full potential of autonomous vehicle technology,” said Bryan Salesky, CEO and Cofounder of Argo AI. “CMU and now Argo AI are two big reasons why Pittsburgh will remain the center of the universe for self-driving technology.”
Deva Ramanan, an Associate Professor in the Robotics Institute who also serves as machine learning lead at Argo AI, will be the center’s principal investigator. The center’s research will involve faculty members and students from across CMU. The center will give students access to the fleet-scale data sets, vehicles, and large-scale infrastructure that are crucial for advancing self-driving technologies and that otherwise would be difficult to obtain.
The center's research is expected to address a number of technical topics, including smart sensor fusion, 3D scene understanding, urban scene simulation, map-based perception, imitation and reinforcement learning, behavioral prediction, and robust validation of software. Research findings will be reported in open scientific literature for use by the entire field.