Despite years of work on robot locomotion, we still do not have robots that can reliably and flexibly move around in homes, workspaces, and natural terrain. For many of these environments, legged robots, as opposed to wheel-based robots, appear to be the most viable option for achieving the desired level of locomotion autonomy. This talk will present recent advances by the Dynamic Robot Laboratory at Oregon State University that brings us much closer to achieving reliable bipedal robot locomotion in natural environments. These advances are a result of combining carefully engineered "animal-like" robot legs with machine learning for teaching the robot to control the legs. This novel approach has allowed for the Cassie robot, developed by Agility Robotics, to reliably stand, walk, run, hop, skip, traverse stairs, and handle novel disturbances in the environment. Most recently this learning approach allowed Cassie to be the first robot to successfully complete a 5K. The talk will cover the journey to these recent results and highlight important general principles that can apply to other engineering control problems.
Alan Fern is a Professor of Computer Science and Associate Head of Research for the School of EECS at Oregon State University. He received his Ph.D. (2004) in Computer Engineering from Purdue University, and his B.S. (1997) in Electrical Engineering from the University of Maine. His research interests span a variety of topics in Artificial Intelligence and Robotics with a particular emphasis on building systems that can learn from experience. He co-directs the Dynamic Robotics Laboratory with Jonathan Hurst at Oregon State and is PI for a number of government funded projects including DARPA programs on Explainable Artificial Intelligence and Machine Common Sense. Most recently he is serving as the OSU lead PI for a new $20M AI Institute on Agricultural AI in collaboration with Washington State University.