Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Zhang, Lintong"'
This paper introduces and assesses a cross-modal global visual localization system that can localize camera images within a color 3D map representation built using both visual and lidar sensing. We present three different state-of-the-art methods for
Externí odkaz:
http://arxiv.org/abs/2408.11966
Exoskeletons for daily use by those with mobility impairments are being developed. They will require accurate and robust scene understanding systems. Current research has used vision to identify immediate terrain and geometric obstacles, however thes
Externí odkaz:
http://arxiv.org/abs/2403.14320
We present LiSTA (LiDAR Spatio-Temporal Analysis), a system to detect probabilistic object-level change over time using multi-mission SLAM. Many applications require such a system, including construction, robotic navigation, long-term autonomy, and e
Externí odkaz:
http://arxiv.org/abs/2403.02175
Versatile and adaptive semantic understanding would enable autonomous systems to comprehend and interact with their surroundings. Existing fixed-class models limit the adaptability of indoor mobile and assistive autonomous systems. In this work, we i
Externí odkaz:
http://arxiv.org/abs/2309.15065
Publikováno v:
Robotics: Science and Systems (RSS) 2023
Localization for autonomous robots in prior maps is crucial for their functionality. This paper offers a solution to this problem for indoor environments called InstaLoc, which operates on an individual lidar scan to localize it within a prior map. W
Externí odkaz:
http://arxiv.org/abs/2305.09552
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
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
Autor:
Zhang, Lintong, Kong, Xiangzeng, Chen, Linjie, Zhang, Wenqing, Lin, Xiyang, Wang, Chuxin, Jiang, Yilun, Li, Jining, Qu, Fangfang
Publikováno v:
In Sensors and Actuators: B. Chemical 15 November 2024 419
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