no code implementations • 23 May 2023 • Mark Van der Merwe, Youngsun Wi, Dmitry Berenson, Nima Fazeli
Representing the object geometry and contact with the environment implicitly allows a single model to predict contact patches of varying complexity.
1 code implementation • 14 May 2023 • Sheng Zhong, Nima Fazeli, Dmitry Berenson
Rather than attempting to estimate the true pose of the object, which is not tractable without a large number of contacts, we seek to estimate a plausible set of poses which obey the constraints imposed by the sensor data.
1 code implementation • 30 Sep 2022 • Yizhou Chen, Andrea Sipos, Mark Van der Merwe, Nima Fazeli
Learning representations in the joint domain of vision and touch can improve manipulation dexterity, robustness, and sample-complexity by exploiting mutual information and complementary cues.
1 code implementation • 23 Oct 2020 • Sheng Zhong, Zhenyuan Zhang, Nima Fazeli, Dmitry Berenson
We propose an approach to online model adaptation and control in the challenging case of hybrid and discontinuous dynamics where actions may lead to difficult-to-escape "trap" states, under a given controller.
no code implementations • 13 Apr 2019 • Anurag Ajay, Maria Bauza, Jiajun Wu, Nima Fazeli, Joshua B. Tenenbaum, Alberto Rodriguez, Leslie P. Kaelbling
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 analytically.
no code implementations • 9 Aug 2018 • Anurag Ajay, Jiajun Wu, Nima Fazeli, Maria Bauza, Leslie P. Kaelbling, Joshua B. Tenenbaum, Alberto Rodriguez
An efficient, generalizable physical simulator with universal uncertainty estimates has wide applications in robot state estimation, planning, and control.
3 code implementations • 3 Oct 2017 • Andy Zeng, Shuran Song, Kuan-Ting Yu, Elliott Donlon, Francois R. Hogan, Maria Bauza, Daolin Ma, Orion Taylor, Melody Liu, Eudald Romo, Nima Fazeli, Ferran Alet, Nikhil Chavan Dafle, Rachel Holladay, Isabella Morona, Prem Qu Nair, Druck Green, Ian Taylor, Weber Liu, Thomas Funkhouser, Alberto Rodriguez
Since product images are readily available for a wide range of objects (e. g., from the web), the system works out-of-the-box for novel objects without requiring any additional training data.