Zobrazeno 1 - 10
of 1 113
pro vyhledávání: '"Kobayashi, Masato IN"'
Autor:
Hirota, Akihiko, Koda, Jin, Egusa, Fumi, Sawada, Tsuyoshi, Sakamoto, Kazushi, Heyer, Mark, Lee, Amanda M, Maeda, Fumiya, Boissier, Samuel, Calzetti, Daniela, Elmegreen, Bruce G., Harada, Nanase, Ho, Luis C., Kobayashi, Masato I. N., Kuno, Nario, Madore, Barry F., Martín, Sergio, Meyer, Jennifer Donovan, Muraoka, Kazuyuki, Watanabe, Yoshimasa
We present a catalog of clouds identified from the $^{12}$CO (1--0) data of M83, which was observed using Atacama Large Millimeter/submillimeter Array (ALMA) with a spatial resolution of $\sim$46 pc and a mass sensitivity of $\sim$10$^4$ $M_{\odot}$
Externí odkaz:
http://arxiv.org/abs/2410.05424
Autonomous robot manipulation is a complex and continuously evolving robotics field. This paper focuses on data augmentation methods in imitation learning. Imitation learning consists of three stages: data collection from experts, learning model, and
Externí odkaz:
http://arxiv.org/abs/2410.04370
Autor:
Konishi, Ayu, Muraoka, Kazuyuki, Tokuda, Kazuki, Fujita, Shinji, Fukui, Yasuo, Yamada, Rin I., Demachi, Fumika, Tachihara, Kengo, Kobayashi, Masato I. N., Kuno, Nario, Tsuge, Kisetsu, Sano, Hidetoshi, Miura, Rie E., Kawamura, Akiko, Onishi, Toshikazu
The evolution of giant molecular clouds (GMCs), the main sites of high-mass star formation, is an essential process to unravel the galaxy evolution. Using a GMC catalogue of M33 from ALMA-ACA survey, we classified 848 GMCs into three types based on t
Externí odkaz:
http://arxiv.org/abs/2407.17018
Autor:
Kobayashi, Masato, Motoi, Naoki
Publikováno v:
IEEE Transactions on Industry Applications, vol. 60, no. 1, pp. 1695-1704, Jan.-Feb. 2024
This paper proposes a navigation method considering blind spots based on the robot operating system (ROS) navigation stack and blind spots layer (BSL) for a wheeled mobile robot. In this paper, environmental information is recognized using a laser ra
Externí odkaz:
http://arxiv.org/abs/2405.05479
Recent advancements in robotics have led to the development of numerous interfaces to enhance the intuitiveness of robot navigation. However, the reliance on traditional 2D displays imposes limitations on the simultaneous visualization of information
Externí odkaz:
http://arxiv.org/abs/2403.19310
Autonomous manipulation in robot arms is a complex and evolving field of study in robotics. This paper proposes work stands at the intersection of two innovative approaches in the field of robotics and machine learning. Inspired by the Action Chunkin
Externí odkaz:
http://arxiv.org/abs/2401.17698
Autonomous manipulation in robot arms is a complex and evolving field of study in robotics. This paper introduces an innovative approach to this challenge by focusing on imitation learning (IL). Unlike traditional imitation methods, our approach uses
Externí odkaz:
http://arxiv.org/abs/2401.16653
Autor:
Wang, Jia-Wei, Koch, Patrick M., Clarke, Seamus D., Fuller, Gary, Peretto, Nicolas, Tang, Ya-Wen, Yen, Hsi-Wei, Lai, Shih-Ping, Ohashi, Nagayoshi, Arzoumanian, Doris, Johnstone, Doug, Furuya, Ray, Inutsuka, Shu-ichiro, Lee, Chang Won, Ward-Thompson, Derek, Gouellec, Valentin J. M. Le, Liu, Hong-Li, Fanciullo, Lapo, Hwang, Jihye, Pattle, Kate, Poidevin, Frédérick, Tahani, Mehrnoosh, Onaka, Takashi, Rawlings, Mark G., Chung, Eun Jung, Liu, Junhao, Lyo, A-Ran, Priestley, Felix, Hoang, Thiem, Tamura, Motohide, Berry, David, Bastien, Pierre, Ching, Tao-Chung, Coudé, Simon, Kwon, Woojin, Chen, Mike, Eswaraiah, Chakali, Soam, Archana, Hasegawa, Tetsuo, Qiu, Keping, Bourke, Tyler L., Byun, Do-Young, Chen, Zhiwei, Chen, Huei-Ru Vivien, Chen, Wen Ping, Cho, Jungyeon, Choi, Minho, Choi, Yunhee, Choi, Youngwoo, Chrysostomou, Antonio, Dai, Sophia, Di Francesco, James, Diep, Pham Ngoc, Doi, Yasuo, Duan, Yan, Duan, Hao-Yuan, Eden, David, Fiege, Jason, Fissel, Laura M., Franzmann, Erica, Friberg, Per, Friesen, Rachel, Gledhill, Tim, Graves, Sarah, Greaves, Jane, Griffin, Matt, Gu, Qilao, Han, Ilseung, Hayashi, Saeko, Houde, Martin, Inoue, Tsuyoshi, Iwasaki, Kazunari, Jeong, Il-Gyo, Könyves, Vera, Kang, Ji-hyun, Kang, Miju, Karoly, Janik, Kataoka, Akimasa, Kawabata, Koji, Khan, Zacariyya, Kim, Mi-Ryang, Kim, Kee-Tae, Kim, Kyoung Hee, Kim, Shinyoung, Kim, Jongsoo, Kim, Hyosung, Kim, Gwanjeong, Kirchschlager, Florian, Kirk, Jason, Kobayashi, Masato I. N., Kusune, Takayoshi, Kwon, Jungmi, Lacaille, Kevin, Law, Chi-Yan, Lee, Sang-Sung, Lee, Hyeseung, Lee, Jeong-Eun, Lee, Chin-Fei, Li, Dalei, Li, Hua-bai, Li, Guangxing, Li, Di, Lin, Sheng-Jun, Liu, Tie, Liu, Sheng-Yuan, Lu, Xing, Mairs, Steve, Matsumura, Masafumi, Matthews, Brenda, Moriarty-Schieven, Gerald, Nagata, Tetsuya, Nakamura, Fumitaka, Nakanishi, Hiroyuki, Ngoc, Nguyen Bich, Park, Geumsook, Parsons, Harriet, Pyo, Tae-Soo, Qian, Lei, Rao, Ramprasad, Rawlings, Jonathan, Retter, Brendan, Richer, John, Rigby, Andrew, Sadavoy, Sarah, Saito, Hiro, Savini, Giorgio, Seta, Masumichi, Sharma, Ekta, Shimajiri, Yoshito, Shinnaga, Hiroko, Tang, Xindi, Thuong, Hoang Duc, Tomisaka, Kohji, Tram, Le Ngoc, Tsukamoto, Yusuke, Viti, Serena, Wang, Hongchi, Whitworth, Anthony, Wu, Jintai, Xie, Jinjin, Yang, Meng-Zhe, Yoo, Hyunju, Yuan, Jinghua, Yun, Hyeong-Sik, Zenko, Tetsuya, Zhang, Chuan-Peng, Zhang, Yapeng, Zhang, Guoyin, Zhou, Jianjun, Zhu, Lei, de Looze, Ilse, André, Philippe, Dowell, C. Darren, Eyres, Stewart, Falle, Sam, Robitaille, Jean-François, van Loo, Sven
We report 850 $\mu$m continuum polarization observations toward the filamentary high-mass star-forming region NGC 2264, taken as part of the B-fields In STar forming Regions Observations (BISTRO) large program on the James Clerk Maxwell Telescope (JC
Externí odkaz:
http://arxiv.org/abs/2401.12728
Autor:
Tsuji, Chikaha, Komukai, Dai, Shirasaka, Mimo, Wada, Hikaru, Omija, Tsunekazu, Horo, Aoi, Furuta, Daiki, Yamaguchi, Saki, Ikoma, So, Tsunashima, Soshi, Kobayashi, Masato, Ishimoto, Koki, Ikeda, Yuya, Matsushima, Tatsuya, Iwasawa, Yusuke, Matsuo, Yutaka
Our team, TRAIL, consists of AI/ML laboratory members from The University of Tokyo. We leverage our extensive research experience in state-of-the-art machine learning to build general-purpose in-home service robots. We previously participated in two
Externí odkaz:
http://arxiv.org/abs/2310.03913
Autor:
Kuroki, So, Guo, Jiaxian, Matsushima, Tatsuya, Okubo, Takuya, Kobayashi, Masato, Ikeda, Yuya, Takanami, Ryosuke, Yoo, Paul, Matsuo, Yutaka, Iwasawa, Yusuke
Due to the inherent uncertainty in their deformability during motion, previous methods in deformable object manipulation, such as rope and cloth, often required hundreds of real-world demonstrations to train a manipulation policy for each object, whi
Externí odkaz:
http://arxiv.org/abs/2309.09051