Zobrazeno 1 - 10
of 1 671
pro vyhledávání: '"A. Camurri"'
Patellofemoral joint (PFJ) issues affect one in four people, with 20% experiencing chronic knee pain despite treatment. Poor outcomes and pain after knee replacement surgery are often linked to patellar mal-tracking. Traditional imaging methods like
Externí odkaz:
http://arxiv.org/abs/2404.15847
Autor:
Emanuele Seminerio, Wanda Morganti, Marina Barbagelata, Sanket Rajeev Sabharwal, Simone Ghisio, Camilla Prete, Barbara Senesi, Simone Dini, Romina Custureri, Simonetta Galliani, Simona Morelli, Gianluca Puleo, Carlo Berutti-Bergotto, Antonio Camurri, Alberto Pilotto, PRO-HOME Project Investigators Group
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract An interconnected system employing Kinect Azure and Fitbit Sense for continuous and non-intrusive data collection was used in the PRO-HOME protected discharge program, aiming at monitoring functional and clinical parameters in hospitalized o
Externí odkaz:
https://doaj.org/article/b25a6f779295451780ebb27b08e273a6
Visual Inertial Odometry (VIO) is one of the most established state estimation methods for mobile platforms. However, when visual tracking fails, VIO algorithms quickly diverge due to rapid error accumulation during inertial data integration. This er
Externí odkaz:
http://arxiv.org/abs/2211.04517
Accurate localization is a core component of a robot's navigation system. To this end, global navigation satellite systems (GNSS) can provide absolute measurements outdoors and, therefore, eliminate long-term drift. However, fusing GNSS data with oth
Externí odkaz:
http://arxiv.org/abs/2209.14649
Autor:
Zhang, Lintong, Helmberger, Michael, Fu, Lanke Frank Tarimo, Wisth, David, Camurri, Marco, Scaramuzza, Davide, Fallon, Maurice
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 8, Issue: 1, January 2023)
Simultaneous Localization and Mapping (SLAM) is being deployed in real-world applications, however many state-of-the-art solutions still struggle in many common scenarios. A key necessity in progressing SLAM research is the availability of high-quali
Externí odkaz:
http://arxiv.org/abs/2208.09825
Autor:
Tranzatto, Marco, Dharmadhikari, Mihir, Bernreiter, Lukas, Camurri, Marco, Khattak, Shehryar, Mascarich, Frank, Pfreundschuh, Patrick, Wisth, David, Zimmermann, Samuel, Kulkarni, Mihir, Reijgwart, Victor, Casseau, Benoit, Homberger, Timon, De Petris, Paolo, Ott, Lionel, Tubby, Wayne, Waibel, Gabriel, Nguyen, Huan, Cadena, Cesar, Buchanan, Russell, Wellhausen, Lorenz, Khedekar, Nikhil, Andersson, Olov, Zhang, Lintong, Miki, Takahiro, Dang, Tung, Mattamala, Matias, Montenegro, Markus, Meyer, Konrad, Wu, Xiangyu, Briod, Adrien, Mueller, Mark, Fallon, Maurice, Siegwart, Roland, Hutter, Marco, Alexis, Kostas
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably
Externí odkaz:
http://arxiv.org/abs/2207.04914
Autor:
Tranzatto, Marco, Mascarich, Frank, Bernreiter, Lukas, Godinho, Carolina, Camurri, Marco, Khattak, Shehryar, Dang, Tung, Reijgwart, Victor, Loeje, Johannes, Wisth, David, Zimmermann, Samuel, Nguyen, Huan, Fehr, Marius, Solanka, Lukas, Buchanan, Russell, Bjelonic, Marko, Khedekar, Nikhil, Valceschini, Mathieu, Jenelten, Fabian, Dharmadhikari, Mihir, Homberger, Timon, De Petris, Paolo, Wellhausen, Lorenz, Kulkarni, Mihir, Miki, Takahiro, Hirsch, Satchel, Montenegro, Markus, Papachristos, Christos, Tresoldi, Fabian, Carius, Jan, Valsecchi, Giorgio, Lee, Joonho, Meyer, Konrad, Wu, Xiangyu, Nieto, Juan, Smith, Andy, Hutter, Marco, Siegwart, Roland, Mueller, Mark, Fallon, Maurice, Alexis, Kostas
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy hard to achieve. This has motivated the DARPA Subterranean Challenge, w
Externí odkaz:
http://arxiv.org/abs/2201.07067
We present a multi-camera LiDAR inertial dataset of 4.5 km walking distance as an expansion of the Newer College Dataset. The global shutter multi-camera device is hardware synchronized with both the IMU and LiDAR, which is more accurate than the ori
Externí odkaz:
http://arxiv.org/abs/2112.08854
This paper introduces a novel proprioceptive state estimator for legged robots based on a learned displacement measurement from IMU data. Recent research in pedestrian tracking has shown that motion can be inferred from inertial data using convolutio
Externí odkaz:
http://arxiv.org/abs/2111.00789
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 7, Issue: 2, April 2022)
We present a multi-camera visual-inertial odometry system based on factor graph optimization which estimates motion by using all cameras simultaneously while retaining a fixed overall feature budget. We focus on motion tracking in challenging environ
Externí odkaz:
http://arxiv.org/abs/2109.05975