539 citations · 2k across the 41 of their papers we have counts for
7 papers · 1 filter
What Robot do I Need? Fast Co-Adaptation of Morphology and Control using Graph Neural Networks
Kevin Sebastian Luck, Roberto Calandra, Michael Mistry
The co-adaptation of robot morphology and behaviour becomes increasingly important with the advent of fast 3D-manufacturing methods and efficient deep reinforcement learning algori…
Active 3D Shape Reconstruction from Vision and Touch
Edward J. Smith, David Meger, Luis Pineda +4
Humans build 3D understandings of the world through active object exploration, using jointly their senses of vision and touch. However, in 3D shape reconstruction, most recent prog…
Towards Learning to Play Piano with Dexterous Hands and Touch
Huazhe Xu, Yuping Luo, Shaoxiong Wang +2
The virtuoso plays the piano with passion, poetry and extraordinary technical ability. As Liszt said (a virtuoso)must call up scent and blossom, and breathe the breath of life. The…
PyTouch: A Machine Learning Library for Touch Processing
Mike Lambeta, Huazhe Xu, Jingwei Xu +4
With the increased availability of rich tactile sensors, there is an equally proportional need for open-source and integrated software capable of efficiently and effectively proces…
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
Luis Pineda, Brandon Amos, Amy Zhang +2
Model-based reinforcement learning is a compelling framework for data-efficient learning of agents that interact with the world. This family of algorithms has many subcomponents th…
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
Baohe Zhang, Raghu Rajan, Luis Pineda +5
Model-based Reinforcement Learning (MBRL) is a promising framework for learning control in a data-efficient manner. MBRL algorithms can be fairly complex due to the separate dynami…
Model-Invariant State Abstractions for Model-Based Reinforcement Learning
Manan Tomar, Amy Zhang, Roberto Calandra +2
Accuracy and generalization of dynamics models is key to the success of model-based reinforcement learning (MBRL). As the complexity of tasks increases, so does the sample ineffici…