Zobrazeno 1 - 10
of 301
pro vyhledávání: '"Ramamoorthy, Subramanian"'
Learning from Demonstration (LfD) is a useful paradigm for training policies that solve tasks involving complex motions. In practice, the successful application of LfD requires overcoming error accumulation during policy execution, i.e. the problem o
Externí odkaz:
http://arxiv.org/abs/2409.18768
This paper addresses a challenging interactive task learning scenario we call rearrangement under unawareness: to manipulate a rigid-body environment in a context where the robot is unaware of a concept that's key to solving the instructed task. We p
Externí odkaz:
http://arxiv.org/abs/2409.17755
Vision-based motion estimation methods show promise in accurately and unobtrusively estimating human body motion for healthcare purposes. However, these methods are not specifically designed for healthcare purposes and face challenges in real-world a
Externí odkaz:
http://arxiv.org/abs/2408.09409
Autor:
Long-fei, Chen, Raza, Muhammad Ahmed, Innes, Craig, Ramamoorthy, Subramanian, Fisher, Robert B.
Aging and chronic conditions affect older adults' daily lives, making early detection of developing health issues crucial. Weakness, common in many conditions, alters physical movements and daily activities subtly. However, detecting such changes can
Externí odkaz:
http://arxiv.org/abs/2406.10045
Autor:
Tsagkas, Nikolaos, Rome, Jack, Ramamoorthy, Subramanian, Mac Aodha, Oisin, Lu, Chris Xiaoxuan
Precise manipulation that is generalizable across scenes and objects remains a persistent challenge in robotics. Current approaches for this task heavily depend on having a significant number of training instances to handle objects with pronounced vi
Externí odkaz:
http://arxiv.org/abs/2403.14526
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:
Innes, Craig, Ramamoorthy, Subramanian
Autonomous Vehicles (AVs) are often tested in simulation to estimate the probability they will violate safety specifications. Two common issues arise when using existing techniques to produce this estimation: If violations occur rarely, simple Monte-
Externí odkaz:
http://arxiv.org/abs/2405.15771
Autor:
Collaboration, Open X-Embodiment, O'Neill, Abby, Rehman, Abdul, Gupta, Abhinav, Maddukuri, Abhiram, Gupta, Abhishek, Padalkar, Abhishek, Lee, Abraham, Pooley, Acorn, Gupta, Agrim, Mandlekar, Ajay, Jain, Ajinkya, Tung, Albert, Bewley, Alex, Herzog, Alex, Irpan, Alex, Khazatsky, Alexander, Rai, Anant, Gupta, Anchit, Wang, Andrew, Kolobov, Andrey, Singh, Anikait, Garg, Animesh, Kembhavi, Aniruddha, Xie, Annie, Brohan, Anthony, Raffin, Antonin, Sharma, Archit, Yavary, Arefeh, Jain, Arhan, Balakrishna, Ashwin, Wahid, Ayzaan, Burgess-Limerick, Ben, Kim, Beomjoon, Schölkopf, Bernhard, Wulfe, Blake, Ichter, Brian, Lu, Cewu, Xu, Charles, Le, Charlotte, Finn, Chelsea, Wang, Chen, Xu, Chenfeng, Chi, Cheng, Huang, Chenguang, Chan, Christine, Agia, Christopher, Pan, Chuer, Fu, Chuyuan, Devin, Coline, Xu, Danfei, Morton, Daniel, Driess, Danny, Chen, Daphne, Pathak, Deepak, Shah, Dhruv, Büchler, Dieter, Jayaraman, Dinesh, Kalashnikov, Dmitry, Sadigh, Dorsa, Johns, Edward, Foster, Ethan, Liu, Fangchen, Ceola, Federico, Xia, Fei, Zhao, Feiyu, Frujeri, Felipe Vieira, Stulp, Freek, Zhou, Gaoyue, Sukhatme, Gaurav S., Salhotra, Gautam, Yan, Ge, Feng, Gilbert, Schiavi, Giulio, Berseth, Glen, Kahn, Gregory, Yang, Guangwen, Wang, Guanzhi, Su, Hao, Fang, Hao-Shu, Shi, Haochen, Bao, Henghui, Amor, Heni Ben, Christensen, Henrik I, Furuta, Hiroki, Bharadhwaj, Homanga, Walke, Homer, Fang, Hongjie, Ha, Huy, Mordatch, Igor, Radosavovic, Ilija, Leal, Isabel, Liang, Jacky, Abou-Chakra, Jad, Kim, Jaehyung, Drake, Jaimyn, Peters, Jan, Schneider, Jan, Hsu, Jasmine, Vakil, Jay, Bohg, Jeannette, Bingham, Jeffrey, Wu, Jeffrey, Gao, Jensen, Hu, Jiaheng, Wu, Jiajun, Wu, Jialin, Sun, Jiankai, Luo, Jianlan, Gu, Jiayuan, Tan, Jie, Oh, Jihoon, Wu, Jimmy, Lu, Jingpei, Yang, Jingyun, Malik, Jitendra, Silvério, João, Hejna, Joey, Booher, Jonathan, Tompson, Jonathan, Yang, Jonathan, Salvador, Jordi, Lim, Joseph J., Han, Junhyek, Wang, Kaiyuan, Rao, Kanishka, Pertsch, Karl, Hausman, Karol, Go, Keegan, Gopalakrishnan, Keerthana, Goldberg, Ken, Byrne, Kendra, Oslund, Kenneth, Kawaharazuka, Kento, Black, Kevin, Lin, Kevin, Zhang, Kevin, Ehsani, Kiana, Lekkala, Kiran, Ellis, Kirsty, Rana, Krishan, Srinivasan, Krishnan, Fang, Kuan, Singh, Kunal Pratap, Zeng, Kuo-Hao, Hatch, Kyle, Hsu, Kyle, Itti, Laurent, Chen, Lawrence Yunliang, Pinto, Lerrel, Fei-Fei, Li, Tan, Liam, Fan, Linxi "Jim", Ott, Lionel, Lee, Lisa, Weihs, Luca, Chen, Magnum, Lepert, Marion, Memmel, Marius, Tomizuka, Masayoshi, Itkina, Masha, Castro, Mateo Guaman, Spero, Max, Du, Maximilian, Ahn, Michael, Yip, Michael C., Zhang, Mingtong, Ding, Mingyu, Heo, Minho, Srirama, Mohan Kumar, Sharma, Mohit, Kim, Moo Jin, Kanazawa, Naoaki, Hansen, Nicklas, Heess, Nicolas, Joshi, Nikhil J, Suenderhauf, Niko, Liu, Ning, Di Palo, Norman, Shafiullah, Nur Muhammad Mahi, Mees, Oier, Kroemer, Oliver, Bastani, Osbert, Sanketi, Pannag R, Miller, Patrick "Tree", Yin, Patrick, Wohlhart, Paul, Xu, Peng, Fagan, Peter David, Mitrano, Peter, Sermanet, Pierre, Abbeel, Pieter, Sundaresan, Priya, Chen, Qiuyu, Vuong, Quan, Rafailov, Rafael, Tian, Ran, Doshi, Ria, Mart'in-Mart'in, Roberto, Baijal, Rohan, Scalise, Rosario, Hendrix, Rose, Lin, Roy, Qian, Runjia, Zhang, Ruohan, Mendonca, Russell, Shah, Rutav, Hoque, Ryan, Julian, Ryan, Bustamante, Samuel, Kirmani, Sean, Levine, Sergey, Lin, Shan, Moore, Sherry, Bahl, Shikhar, Dass, Shivin, Sonawani, Shubham, Tulsiani, Shubham, Song, Shuran, Xu, Sichun, Haldar, Siddhant, Karamcheti, Siddharth, Adebola, Simeon, Guist, Simon, Nasiriany, Soroush, Schaal, Stefan, Welker, Stefan, Tian, Stephen, Ramamoorthy, Subramanian, Dasari, Sudeep, Belkhale, Suneel, Park, Sungjae, Nair, Suraj, Mirchandani, Suvir, Osa, Takayuki, Gupta, Tanmay, Harada, Tatsuya, Matsushima, Tatsuya, Xiao, Ted, Kollar, Thomas, Yu, Tianhe, Ding, Tianli, Davchev, Todor, Zhao, Tony Z., Armstrong, Travis, Darrell, Trevor, Chung, Trinity, Jain, Vidhi, Kumar, Vikash, Vanhoucke, Vincent, Zhan, Wei, Zhou, Wenxuan, Burgard, Wolfram, Chen, Xi, Chen, Xiangyu, Wang, Xiaolong, Zhu, Xinghao, Geng, Xinyang, Liu, Xiyuan, Liangwei, Xu, Li, Xuanlin, Pang, Yansong, Lu, Yao, Ma, Yecheng Jason, Kim, Yejin, Chebotar, Yevgen, Zhou, Yifan, Zhu, Yifeng, Wu, Yilin, Xu, Ying, Wang, Yixuan, Bisk, Yonatan, Dou, Yongqiang, Cho, Yoonyoung, Lee, Youngwoon, Cui, Yuchen, Cao, Yue, Wu, Yueh-Hua, Tang, Yujin, Zhu, Yuke, Zhang, Yunchu, Jiang, Yunfan, Li, Yunshuang, Li, Yunzhu, Iwasawa, Yusuke, Matsuo, Yutaka, Ma, Zehan, Xu, Zhuo, Cui, Zichen Jeff, Zhang, Zichen, Fu, Zipeng, Lin, Zipeng
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretra
Externí odkaz:
http://arxiv.org/abs/2310.08864
In surgery, the application of appropriate force levels is critical for the success and safety of a given procedure. While many studies are focused on measuring in situ forces, little attention has been devoted to relating these observed forces to su
Externí odkaz:
http://arxiv.org/abs/2309.12219
A key goal of the System-Theoretic Process Analysis (STPA) hazard analysis technique is the identification of loss scenarios - causal factors that could potentially lead to an accident. We propose an approach that aims to assist engineers in identify
Externí odkaz:
http://arxiv.org/abs/2306.04499