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pro vyhledávání: '"Mukadam A"'
Autor:
Fu, Letian, Datta, Gaurav, Huang, Huang, Panitch, William Chung-Ho, Drake, Jaimyn, Ortiz, Joseph, Mukadam, Mustafa, Lambeta, Mike, Calandra, Roberto, Goldberg, Ken
Touch is an important sensing modality for humans, but it has not yet been incorporated into a multimodal generative language model. This is partially due to the difficulty of obtaining natural language labels for tactile data and the complexity of a
Externí odkaz:
http://arxiv.org/abs/2402.13232
Autor:
Suresh, Sudharshan, Qi, Haozhi, Wu, Tingfan, Fan, Taosha, Pineda, Luis, Lambeta, Mike, Malik, Jitendra, Kalakrishnan, Mrinal, Calandra, Roberto, Kaess, Michael, Ortiz, Joseph, Mukadam, Mustafa
To achieve human-level dexterity, robots must infer spatial awareness from multimodal sensing to reason over contact interactions. During in-hand manipulation of novel objects, such spatial awareness involves estimating the object's pose and shape. T
Externí odkaz:
http://arxiv.org/abs/2312.13469
Deep learning models are often deployed in downstream tasks that the training procedure may not be aware of. For example, models solely trained to achieve accurate predictions may struggle to perform well on downstream tasks because seemingly small p
Externí odkaz:
http://arxiv.org/abs/2312.05250
Robotic manipulation tasks such as object insertion typically involve interactions between object and environment, namely extrinsic contacts. Prior work on Neural Contact Fields (NCF) use intrinsic tactile sensing between gripper and object to estima
Externí odkaz:
http://arxiv.org/abs/2309.16652
Autor:
Fan, Taosha, Ortiz, Joseph, Hsiao, Ming, Monge, Maurizio, Dong, Jing, Murphey, Todd, Mukadam, Mustafa
Scaling to arbitrarily large bundle adjustment problems requires data and compute to be distributed across multiple devices. Centralized methods in prior works are only able to solve small or medium size problems due to overhead in computation and co
Externí odkaz:
http://arxiv.org/abs/2305.07026
Publikováno v:
Global Journal on Quality and Safety in Healthcare, Vol 7, Iss 3, Pp 115-117 (2024)
Externí odkaz:
https://doaj.org/article/46d9467563354590943b46b17f5327b3
Autor:
Bolte, Benjamin, Wang, Austin, Yang, Jimmy, Mukadam, Mustafa, Kalakrishnan, Mrinal, Paxton, Chris
In order for robots to follow open-ended instructions like "go open the brown cabinet over the sink", they require an understanding of both the scene geometry and the semantics of their environment. Robotic systems often handle these through separate
Externí odkaz:
http://arxiv.org/abs/2304.12164
Simulating vision-based tactile sensors enables learning models for contact-rich tasks when collecting real world data at scale can be prohibitive. However, modeling the optical response of the gel deformation as well as incorporating the dynamics of
Externí odkaz:
http://arxiv.org/abs/2304.01182
We formulate grasp learning as a neural field and present Neural Grasp Distance Fields (NGDF). Here, the input is a 6D pose of a robot end effector and output is a distance to a continuous manifold of valid grasps for an object. In contrast to curren
Externí odkaz:
http://arxiv.org/abs/2211.02647
We present MidasTouch, a tactile perception system for online global localization of a vision-based touch sensor sliding on an object surface. This framework takes in posed tactile images over time, and outputs an evolving distribution of sensor pose
Externí odkaz:
http://arxiv.org/abs/2210.14210