3 papers
cs.RO2020
Long-Horizon Prediction and Uncertainty Propagation with Residual Point Contact Learners
Nima Fazeli, Anurag Ajay, Alberto Rodriguez
The ability to simulate and predict the outcome of contacts is paramount to the successful execution of many robotic tasks. Simulators are powerful tools for the design of robots a…
cs.RO2019
Combining Physical Simulators and Object-Based Networks for Control
Anurag Ajay, Maria Bauza, Jiajun Wu +4
Physics engines play an important role in robot planning and control; however, many real-world control problems involve complex contact dynamics that cannot be characterized analyt…
cs.RO2018
Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing
Anurag Ajay, Jiajun Wu, Nima Fazeli +4
An efficient, generalizable physical simulator with universal uncertainty estimates has wide applications in robot state estimation, planning, and control. In this paper, we build…