Zobrazeno 1 - 10
of 284
pro vyhledávání: '"Navarro, Angel"'
Autor:
Navarro, Angel, Casacuberta, Francisco
Pre-trained large language models (LLM) are starting to be widely used in many applications. In this work, we explore the use of these models in interactive machine translation (IMT) environments. In particular, we have chosen mBART (multilingual Bid
Externí odkaz:
http://arxiv.org/abs/2407.06990
Autor:
Martí-Saumell, Josep, Duarte, Hugo, Grosch, Patrick, Andrade-Cetto, Juan, Santamaria-Navarro, Angel, Solà, Joan
This paper introduces Borinot, an open-source aerial robotic platform designed to conduct research on hybrid agile locomotion and manipulation using flight and contacts. This platform features an agile and powerful hexarotor that can be outfitted wit
Externí odkaz:
http://arxiv.org/abs/2307.14686
This paper introduces Borinot, an open-source flying robotic platform designed to perform hybrid agile locomotion and manipulation. This platform features a compact and powerful hexarotor that can be outfitted with torque-actuated extremities of dive
Externí odkaz:
http://arxiv.org/abs/2305.01423
Autor:
Saboia, Maira, Clark, Lillian, Thangavelu, Vivek, Edlund, Jeffrey A., Otsu, Kyohei, Correa, Gustavo J., Varadharajan, Vivek Shankar, Santamaria-Navarro, Angel, Touma, Thomas, Bouman, Amanda, Melikyan, Hovhannes, Pailevanian, Torkom, Kim, Sung-Kyun, Archanian, Avak, Vaquero, Tiago Stegun, Beltrame, Giovanni, Napp, Nils, Pessin, Gustavo, Agha-mohammadi, Ali-akbar
Communication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-to-base comms improves situational awareness. Exploring comms-restricted (e.g., subterranean
Externí odkaz:
http://arxiv.org/abs/2206.02245
Non-linear model predictive control (nMPC) is a powerful approach to control complex robots (such as humanoids, quadrupeds, or unmanned aerial manipulators (UAMs)) as it brings important advantages over other existing techniques. The full-body dynami
Externí odkaz:
http://arxiv.org/abs/2107.03722
Autor:
Fakoorian, Seyed, Santamaria-Navarro, Angel, Lopez, Brett T., Simon, Dan, Agha-mohammadi, Ali-akbar
This work proposes a resilient and adaptive state estimation framework for robots operating in perceptually-degraded environments. The approach, called Adaptive Maximum Correntropy Criterion Kalman Filtering (AMCCKF), is inherently robust to corrupte
Externí odkaz:
http://arxiv.org/abs/2103.15354
Autor:
Agha, Ali, Otsu, Kyohei, Morrell, Benjamin, Fan, David D., Thakker, Rohan, Santamaria-Navarro, Angel, Kim, Sung-Kyun, Bouman, Amanda, Lei, Xianmei, Edlund, Jeffrey, Ginting, Muhammad Fadhil, Ebadi, Kamak, Anderson, Matthew, Pailevanian, Torkom, Terry, Edward, Wolf, Michael, Tagliabue, Andrea, Vaquero, Tiago Stegun, Palieri, Matteo, Tepsuporn, Scott, Chang, Yun, Kalantari, Arash, Chavez, Fernando, Lopez, Brett, Funabiki, Nobuhiro, Miles, Gregory, Touma, Thomas, Buscicchio, Alessandro, Tordesillas, Jesus, Alatur, Nikhilesh, Nash, Jeremy, Walsh, William, Jung, Sunggoo, Lee, Hanseob, Kanellakis, Christoforos, Mayo, John, Harper, Scott, Kaufmann, Marcel, Dixit, Anushri, Correa, Gustavo, Lee, Carlyn, Gao, Jay, Merewether, Gene, Maldonado-Contreras, Jairo, Salhotra, Gautam, Da Silva, Maira Saboia, Ramtoula, Benjamin, Kubo, Yuki, Fakoorian, Seyed, Hatteland, Alexander, Kim, Taeyeon, Bartlett, Tara, Stephens, Alex, Kim, Leon, Bergh, Chuck, Heiden, Eric, Lew, Thomas, Cauligi, Abhishek, Heywood, Tristan, Kramer, Andrew, Leopold, Henry A., Choi, Chris, Daftry, Shreyansh, Toupet, Olivier, Wee, Inhwan, Thakur, Abhishek, Feras, Micah, Beltrame, Giovanni, Nikolakopoulos, George, Shim, David, Carlone, Luca, Burdick, Joel
This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques uti
Externí odkaz:
http://arxiv.org/abs/2103.11470
Autor:
Tagliabue, Andrea, Tordesillas, Jesus, Cai, Xiaoyi, Santamaria-Navarro, Angel, How, Jonathan P., Carlone, Luca, Agha-mohammadi, Ali-akbar
State estimation for robots navigating in GPS-denied and perceptually-degraded environments, such as underground tunnels, mines and planetary subsurface voids, remains challenging in robotics. Towards this goal, we present LION (Lidar-Inertial Observ
Externí odkaz:
http://arxiv.org/abs/2102.03443
In recent years, unsupervised deep learning approaches have received significant attention to estimate the depth and visual odometry (VO) from unlabelled monocular image sequences. However, their performance is limited in challenging environments due
Externí odkaz:
http://arxiv.org/abs/2011.00341