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A survey on physics informed reinforcement learning: Review and open problems
C Banerjee, K Nguyen, C Fookes, M Raissi - ar**
floating objects from water, rolling an ice cream cone, etc. Using robots to augment or …
floating objects from water, rolling an ice cream cone, etc. Using robots to augment or …
Neuphysics: Editable neural geometry and physics from monocular videos
We present a method for learning 3D geometry and physics parameters of a dynamic scene
from only a monocular RGB video input. To decouple the learning of underlying scene …
from only a monocular RGB video input. To decouple the learning of underlying scene …
Learning quadruped locomotion using differentiable simulation
Y Song, S Kim, D Scaramuzza - arxiv preprint arxiv:2403.14864, 2024 - arxiv.org
This work explores the potential of using differentiable simulation for learning quadruped
locomotion. Differentiable simulation promises fast convergence and stable training by …
locomotion. Differentiable simulation promises fast convergence and stable training by …
Roboninja: Learning an adaptive cutting policy for multi-material objects
We introduce RoboNinja, a learning-based cutting system for multi-material objects (ie, soft
objects with rigid cores such as avocados or mangos). In contrast to prior works using open …
objects with rigid cores such as avocados or mangos). In contrast to prior works using open …