Michael Posa

Michael Posa. He is an American roboticist and associate professor in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania, where he leads the Dynamic Autonomy and Intelligent Robotics (DAIR) Lab. His research focuses on the intersection of control theory, optimization, and machine learning to enable dynamic robotic behaviors in complex environments, with significant contributions to legged robots and dexterous manipulation. Posa's work is characterized by a rigorous mathematical approach to real-world robotic challenges, particularly those involving contact-rich tasks and underactuated systems.

Early life and education

Posa completed his undergraduate studies in Electrical Engineering at the University of Illinois at Urbana–Champaign. He then pursued his graduate education at Stanford University, where he earned both his M.S. and Ph.D. in Electrical Engineering. His doctoral research was conducted under the supervision of Professor Russ Tedrake within the Robot Locomotion Group at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). His dissertation, which laid foundational work for later research, addressed the challenges of optimal control and motion planning for complex robotic systems.

Academic career

Following his Ph.D., Posa held a postdoctoral position at the MIT Laboratory for Information and Decision Systems (LIDS). He subsequently joined the faculty of the University of Pennsylvania in 2016 as an assistant professor, with a primary appointment in the School of Engineering and Applied Science. At Penn, he is a core member of the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory, a leading interdisciplinary robotics research center. He was promoted to associate professor with tenure in 2022, reflecting the significant impact of his research and teaching in the fields of robotics and dynamics.

Research and contributions

Posa's research program is centered on developing algorithms that allow robots to perform dynamic, contact-rich tasks with reliability and efficiency. A major thrust of his work involves creating optimization-based frameworks for motion planning and feedback control that explicitly model the hybrid dynamics inherent in tasks like walking, grasping, and manipulation. He has made notable advances in model predictive control (MPC) for legged locomotion, enabling robots like the MIT Cheetah and other platforms to traverse rough terrain. His lab has also pioneered methods for dexterous manipulation, using tools from convex optimization and reinforcement learning to control robotic hands in complex interaction scenarios. This work has direct applications in logistics, manufacturing, and hazardous environment operation.

Awards and honors

Posa's contributions have been recognized through several prestigious early-career awards. These include the National Science Foundation's CAREER Award for his work on contact-aware robot control and the Defense Advanced Research Projects Agency (DARPA) Young Faculty Award. He has also received recognition from the Office of Naval Research (ONR) through a Young Investigator Program award. His research publications have garnered best paper awards and nominations at major conferences, including the IEEE International Conference on Robotics and Automation (ICRA) and the Robotics: Science and Systems (RSS) conference.

Personal life

Posa maintains a relatively private personal life, with his public profile focused primarily on his academic and research endeavors. He is actively involved in mentoring graduate students and postdoctoral researchers within the GRASP Laboratory and the broader University of Pennsylvania community. His commitment to education extends to developing new courses on dynamic systems and robotic control for engineering students.

Category:American roboticists Category:University of Pennsylvania faculty Category:Stanford University alumni Category:University of Illinois at Urbana–Champaign alumni Category:Living people