Michael Posa
Assistant Professor, MEAM
Michael’s interests center on planning, control, and formal analysis of robots as they interact with the world. Whether a robot is assisting within the home, or operating in a manufacturing plant, the fundamental promise of robotics requires touching and affecting a complex environment in a safe and controlled fashion. Michael focuses on developing computationally tractable algorithms which enable robots to operate both dynamically and safely as they quickly maneuver through and interact with their environments. This research involves understanding the interplay between the non-smooth dynamics of contact and numerical optimization, and then testing these techniques on both legged robots and robotic arms.
Research Areas
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Research Groups
Publications
Instance-Agnostic Geometry and Contact Dynamics Learning
Publisher IEEE
Simultaneous Learning of Contact and Continuous Dynamics
Publisher CoRL
Optimization-Based Control for Dynamic Legged Robots
Publisher IEEE
Validating Robotics Simulators on Real World Impacts
Publisher IEEE
Real-Time Multi-Contact Model Predictive Control via ADMM
Publisher ICRA
Learning Linear Complementarity Systems
Publisher L4DC
Impact Invariant Control with Applications to Bipedal Locomotion
Publisher arXiv
ContactNets: Learning Discontinuous Contact Dynamics with Smooth, Implicit Representations
Publisher CoRL
Contact-Aware Controller Design for Complementarity Systems
Publisher arXiv
Modeling and Analysis of Non-unique Behaviors in Multiple Frictional Impacts
Publisher Robotics: Science and Systems (RSS)
Optimal reduced-order modeling of bipedal locomotion
Publisher arXiv
A Quasi-static Model and Simulation Approach for Pushing, Grasping, and Jamming
Publisher Workshop on the Algorithmic Foundations of Robotics (WAFR)
News
Faculty News
Profs at Penn’s GRASP Lab snagged Toyota Research Institute funding for robotics research
February 1, 2021
Ph.D. Students
Research Staff
Alumni
Research Areas
- Contact Modeling
- Hybrid Systems
- Legged Locomotion
- Manipulation
- Optimal Control
- Autonomy