Recent Research at MIT ACL on Planning and Learning for Robotic Applications

Tuesday, October 7, 2014 - 4:00pm to Wednesday, October 8, 2014 - 3:55pm

Event Calendar Category

LIDS Seminar Series

Speaker Name

Jonathan P. How



Building and Room number



This talk will present recent research on planning and learning for several air and ground robotic applications done at the MIT Aerospace Controls Laboratory (ACL). ACL combines theoretical research on decision making under uncertainty; path planning, activity and task assignment; estimation and navigation; adaptive control, model and policy learning; inverse reinforcement learning, and transfer learning, with the development of advanced robots. A key part of ACL is RAVEN, a large-scale experimental facility that uses Vicon motion capture sensing and a laser projection system to enable rapid prototyping of advanced planning and learning concepts. The effectiveness of RAVEN was demonstrated during the recent multi-UAV persistent surveillance missions that utilized the autonomous battery change/charge capability of our ground stations to enable online learning during the long-duration (5hr) flights. RAVEN also facilitated the development of our variable-pitch quadrotor, which has been used to demonstrate advanced aerobatics. The talk will highlight some of key research developments and show videos of the main experiments.


Dr. Jonathan P. How is the Richard C. Maclaurin Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology.  He received a B.A.Sc. from the University of Toronto in 1987 and his S.M. and Ph.D. in Aeronautics and Astronautics from MIT in 1990 and 1993, respectively. He then studied for two years at MIT as a postdoctoral associate for the Middeck Active Control Experiment (MACE) that flew onboard the Space Shuttle Endeavour in March 1995. Prior to joining MIT in 2000, he was an Assistant Professor in the Department of Aeronautics and Astronautics at Stanford University.

Professor How was the planning and control lead for the MIT DARPA Urban Challenge team that placed fourth in the 2007 race at Victorville, CA.  Other research interests include: (1) Design and implementation of distributed robust planning algorithms to coordinate multiple autonomous vehicles in dynamic uncertain environments; (2) Robust and adaptive control to enable autonomous agile flight and aerobatics; and (3) Reinforcement learning for real-time mechanical and aerospace applications. 

Professor How currently serves as the head of the Information sector within the Department of Aeronautics and Astronautics, and is the Director of the Ford-MIT Alliance. He is the Deputy Editor-in-Chief of the IEEE Control Systems Magazine and an Associate Editor for the AIAA Journal of Aerospace Information Systems. Professor How was the recipient of the 2002 Institute of Navigation Burka Award, a Boeing Special Invention award in 2008, the 2011 IFAC Automatica award for best applications paper, Recipient of the AIAA Best Paper Award from the 2011 and 2012 Guidance Navigation and Control Conferences, and he is an Associate Fellow of AIAA and a senior member of IEEE.