Zobrazeno 1 - 10
of 689
pro vyhledávání: '"Goldberg, Ken"'
Autor:
Wang, Jonathan, Huang, Huang, Lim, Vincent, Zhang, Harry, Ichnowski, Jeffrey, Seita, Daniel, Chen, Yunliang, Goldberg, Ken
Dynamic manipulation of free-end cables has applications for cable management in homes, warehouses and manufacturing plants. We present a supervised learning approach for dynamic manipulation of free-end cables, focusing on the problem of getting the
Externí odkaz:
http://arxiv.org/abs/2405.09581
Autor:
Moghani, Masoud, Doorenbos, Lars, Panitch, William Chung-Ho, Huver, Sean, Azizian, Mahdi, Goldberg, Ken, Garg, Animesh
In this work, we present SuFIA, the first framework for natural language-guided augmented dexterity for robotic surgical assistants. SuFIA incorporates the strong reasoning capabilities of large language models (LLMs) with perception modules to imple
Externí odkaz:
http://arxiv.org/abs/2405.05226
Imitation learning is a promising paradigm for training robot control policies, but these policies can suffer from distribution shift, where the conditions at evaluation time differ from those in the training data. A popular approach for increasing p
Externí odkaz:
http://arxiv.org/abs/2405.01472
Autor:
Yu, Qinxi, Moghani, Masoud, Dharmarajan, Karthik, Schorp, Vincent, Panitch, William Chung-Ho, Liu, Jingzhou, Hari, Kush, Huang, Huang, Mittal, Mayank, Goldberg, Ken, Garg, Animesh
Physics-based simulations have accelerated progress in robot learning for driving, manipulation, and locomotion. Yet, a fast, accurate, and robust surgical simulation environment remains a challenge. In this paper, we present ORBIT-Surgical, a physic
Externí odkaz:
http://arxiv.org/abs/2404.16027
Autor:
Hari, Kush, Kim, Hansoul, Panitch, Will, Srinivas, Kishore, Schorp, Vincent, Dharmarajan, Karthik, Ganti, Shreya, Sadjadpour, Tara, Goldberg, Ken
We present STITCH: an augmented dexterity pipeline that performs Suture Throws Including Thread Coordination and Handoffs. STITCH iteratively performs needle insertion, thread sweeping, needle extraction, suture cinching, needle handover, and needle
Externí odkaz:
http://arxiv.org/abs/2404.05151
Autor:
Khazatsky, Alexander, Pertsch, Karl, Nair, Suraj, Balakrishna, Ashwin, Dasari, Sudeep, Karamcheti, Siddharth, Nasiriany, Soroush, Srirama, Mohan Kumar, Chen, Lawrence Yunliang, Ellis, Kirsty, Fagan, Peter David, Hejna, Joey, Itkina, Masha, Lepert, Marion, Ma, Yecheng Jason, Miller, Patrick Tree, Wu, Jimmy, Belkhale, Suneel, Dass, Shivin, Ha, Huy, Jain, Arhan, Lee, Abraham, Lee, Youngwoon, Memmel, Marius, Park, Sungjae, Radosavovic, Ilija, Wang, Kaiyuan, Zhan, Albert, Black, Kevin, Chi, Cheng, Hatch, Kyle Beltran, Lin, Shan, Lu, Jingpei, Mercat, Jean, Rehman, Abdul, Sanketi, Pannag R, Sharma, Archit, Simpson, Cody, Vuong, Quan, Walke, Homer Rich, Wulfe, Blake, Xiao, Ted, Yang, Jonathan Heewon, Yavary, Arefeh, Zhao, Tony Z., Agia, Christopher, Baijal, Rohan, Castro, Mateo Guaman, Chen, Daphne, Chen, Qiuyu, Chung, Trinity, Drake, Jaimyn, Foster, Ethan Paul, Gao, Jensen, Herrera, David Antonio, Heo, Minho, Hsu, Kyle, Hu, Jiaheng, Jackson, Donovon, Le, Charlotte, Li, Yunshuang, Lin, Kevin, Lin, Roy, Ma, Zehan, Maddukuri, Abhiram, Mirchandani, Suvir, Morton, Daniel, Nguyen, Tony, O'Neill, Abigail, Scalise, Rosario, Seale, Derick, Son, Victor, Tian, Stephen, Tran, Emi, Wang, Andrew E., Wu, Yilin, Xie, Annie, Yang, Jingyun, Yin, Patrick, Zhang, Yunchu, Bastani, Osbert, Berseth, Glen, Bohg, Jeannette, Goldberg, Ken, Gupta, Abhinav, Gupta, Abhishek, Jayaraman, Dinesh, Lim, Joseph J, Malik, Jitendra, Martín-Martín, Roberto, Ramamoorthy, Subramanian, Sadigh, Dorsa, Song, Shuran, Wu, Jiajun, Yip, Michael C., Zhu, Yuke, Kollar, Thomas, Levine, Sergey, Finn, Chelsea
The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. However, creating such datasets is challenging: collecting robot manipul
Externí odkaz:
http://arxiv.org/abs/2403.12945
Autor:
Rashid, Adam, Kim, Chung Min, Kerr, Justin, Fu, Letian, Hari, Kush, Ahmad, Ayah, Chen, Kaiyuan, Huang, Huang, Gualtieri, Marcus, Wang, Michael, Juette, Christian, Tian, Nan, Ren, Liu, Goldberg, Ken
Inventory monitoring in homes, factories, and retail stores relies on maintaining data despite objects being swapped, added, removed, or moved. We introduce Lifelong LERF, a method that allows a mobile robot with minimal compute to jointly optimize a
Externí odkaz:
http://arxiv.org/abs/2403.10494
Autor:
Chen, Lawrence Yunliang, Hari, Kush, Dharmarajan, Karthik, Xu, Chenfeng, Vuong, Quan, Goldberg, Ken
The ability to reuse collected data and transfer trained policies between robots could alleviate the burden of additional data collection and training. While existing approaches such as pretraining plus finetuning and co-training show promise, they d
Externí odkaz:
http://arxiv.org/abs/2402.19249
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:
Fu, Letian, Lian, Long, Wang, Renhao, Shi, Baifeng, Wang, Xudong, Yala, Adam, Darrell, Trevor, Efros, Alexei A., Goldberg, Ken
In this work, we re-examine inter-patch dependencies in the decoding mechanism of masked autoencoders (MAE). We decompose this decoding mechanism for masked patch reconstruction in MAE into self-attention and cross-attention. Our investigations sugge
Externí odkaz:
http://arxiv.org/abs/2401.14391