Dr. Michael Lanighan
Dr. Lanighan’s research focuses on developing planning techniques that enable robots to overcome situational uncertainty. By focusing on salient subsets of state information and mitigating risk, these techniques lead to robust autonomous systems capable of long-term deployments. His thesis work at UMass in hierarchical belief-space planning enabled an autonomous mobile manipulator to execute hundreds of actions while avoiding decision making failures that would have required human intervention. He joined TRACLabs in 2018 after previously participating in the development of the CRAFTSMAN software framework as a graduate intern. He has assisted in the development of CRAFTSMAN applications for NASA Robonaut 2, NASA Valkyrie, and proof-of-concept flexible manufacturing cells. He is currently representing TRACLabs on-site at NASA JSC, furthering the capabilities of the Valkyrie humanoid robot.
2012 B.S. Physics and Computer Science, Canisius College. Buffalo NY
2015 M.S. Computer Science, University of Massachusetts Amherst. Amherst MA
2019 Ph.D. Computer Science, University of Massachusetts Amherst. Amherst MA
M.W. Lanighan and R.A. Grupen. Long-term Autonomous Mobile Manipulation under Uncertainty. In Proceedings of the 2019 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Montreal, Canada, May 2019.
M.W. Lanighan , T. Takahashi, and R.A. Grupen. Planning Robust Manual Tasks in Hierarchical Belief Spaces. In Proceedings of the 28th International Conference on Automated Planning and Scheduling. Delft, The Netherlands, June 2018.
T. Takahashi, M.W. Lanighan , and R.A. Grupen. Intrinsically Motivated Self-Supervised Deep Sensorimotor Learning for Grasping. In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain, October 2018.
T. Takahashi, M.W. Lanighan , and R.A. Grupen. Hybrid Task Planning Grounded in Belief: Constructing Physical Copies of Simple Structures. In Proceedings of the 27th International Conference on Automated Planning and Scheduling. Pittsburgh, PA, USA, June 2017.
D. Ruiken, J.M. Wong, T.Q. Liu, M. Hebert, T. Takahashi, M.W. Lanighan , and R.A. Grupen. Affordance-Based Active Belief: Recognition using Visual and Manual Actions. In Proceedings of the 2016 International Conference on Intelligent Robots and Systems. Daejeon, Korea, October, 2016.
S. Gee, M.W. Lanighan, and B. Ames, and R. Burridge Toward Performing a Filter-Vacuuming Procedure Using a Humanoid Robot on ISS. In Proceedings of The International Symposium on Artificial Intelligence, Robotics and Automation in Space (ISAIRAS). Beijing, China, June 2016.