28 citations · 57 across the 28 of their papers we have counts for
9 papers · 1 filter
Simultaneous Learning of Contact and Continuous Dynamics
Bibit Bianchini, Mathew Halm, Michael Posa
Robotic manipulation can greatly benefit from the data efficiency, robustness, and predictability of model-based methods if robots can quickly generate models of novel objects they…
Reinforcement Learning for Reduced-order Models of Legged Robots
Yu-Ming Chen, Hien Bui, Michael Posa
Model-based approaches for planning and control for bipedal locomotion have a long history of success. It can provide stability and safety guarantees while being effective in accom…
Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning
Wei-Cheng Huang, Alp Aydinoglu, Wanxin Jin +1
The hybrid nature of multi-contact robotic systems, due to making and breaking contact with the environment, creates significant challenges for high-quality control. Existing model…
Enhancing Task Performance of Learned Simplified Models via Reinforcement Learning
Hien Bui, Michael Posa
In contact-rich tasks, the hybrid, multi-modal nature of contact dynamics poses great challenges in model representation, planning, and control. Recent efforts have attempted to ad…
Instance-Agnostic Geometry and Contact Dynamics Learning
Mengti Sun, Bowen Jiang, Bibit Bianchini +2
This work presents an instance-agnostic learning framework that fuses vision with dynamics to simultaneously learn shape, pose trajectories, and physical properties via the use of…
Bipedal Walking on Constrained Footholds with MPC Footstep Control
Brian Acosta, Michael Posa
Bipedal robots promise the ability to traverse rough terrain quickly and efficiently, and indeed, humanoid robots can now use strong ankles and careful foot placement to traverse d…