Michael Posa
Michael Posa is an Associate Professor in Mechanical Engineering and Applied Mechanics at the University of Pennsylvania, where he leads the Dynamic Autonomy and Intelligent Robotics (DAIR) Lab within the Penn GRASP Laboratory. His research focuses on developing algorithms for planning and control that enable robots to operate dynamically and safely in contact-rich environments, with expertise spanning trajectory optimization, contact dynamics, and model-based control. He received his Ph.D. in Electrical Engineering and Computer Science from MIT in 2017 and was awarded the NSF CAREER Award in 2023.
“On hardware, the paper shows cumulative success rates reaching 80% across three feedback iterations, with successes distributed across all three iterations rather than concentrated in the first (Figure 6, Section 5.2).”
Source→“LENS uses a vision-language model (GPT-4o) not to generate actions or plans, but to simplify the scene before any planner or controller runs.”
Source→“The paper demonstrates this works as a front-end across three fundamentally different paradigms — Task and Motion Planning (TAMP), contact-implicit model predictive control (C3+), and the π0.5 vision-language-action model.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.