P
Pascal Gohl
Researcher at Institute of Robotics and Intelligent Systems
Publications - 17
Citations - 1906
Pascal Gohl is an academic researcher from Institute of Robotics and Intelligent Systems. The author has contributed to research in topics: Navigation system & Inertial measurement unit. The author has an hindex of 9, co-authored 17 publications receiving 1327 citations. Previous affiliations of Pascal Gohl include ETH Zurich.
Papers
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Journal ArticleDOI
The EuRoC micro aerial vehicle datasets
Michael Burri,Janosch Nikolic,Pascal Gohl,Thomas Schneider,Joern Rehder,Sammy Omari,Markus W. Achtelik,Roland Siegwart +7 more
TL;DR: Eleven datasets are provided, ranging from slow flights under good visual conditions to dynamic flights with motion blur and poor illumination, enabling researchers to thoroughly test and evaluate their algorithms.
Proceedings ArticleDOI
A synchronized visual-inertial sensor system with FPGA pre-processing for accurate real-time SLAM
Janosch Nikolic,Joern Rehder,Michael Burri,Pascal Gohl,Stefan Leutenegger,Paul Furgale,Roland Siegwart +6 more
TL;DR: This work presents a visual-inertial sensor unit aimed at effortless deployment on robots in order to equip them with robust real-time Simultaneous Localization and Mapping (SLAM) capabilities, and to facilitate research on this important topic at a low entry barrier.
Proceedings ArticleDOI
Visual industrial inspection using aerial robots
TL;DR: A UAV navigation system setup that uses visual-inertial sensor cues to estimate the UAV pose as well as to create a dense 3D map of the environment in real-time onboard the Uav, completely independent of GPS is presented.
Book ChapterDOI
Long-Endurance Sensing and Mapping Using a Hand-Launchable Solar-Powered UAV
Philipp Oettershagen,Thomas Stastny,Thomas Mantel,Amir Melzer,Konrad Rudin,Pascal Gohl,Gabriel Agamennoni,Kostas Alexis,Roland Siegwart +8 more
TL;DR: An endurance analysis shows that AtlantikSolar can provide full-daylight operation and a minimum flight endurance of 8 h throughout the whole year with its full multi-camera mapping payload.
Proceedings ArticleDOI
Dense visual-inertial navigation system for mobile robots
TL;DR: This work proposes an odometry and mapping system that leverages the full photometric information from a stereo-vision system as well as inertial measurements in a probabilistic framework while running in real-time on a single low-power Intel CPU core.