J
Jeffrey A. Delmerico
Researcher at University of Zurich
Publications - 31
Citations - 1825
Jeffrey A. Delmerico is an academic researcher from University of Zurich. The author has contributed to research in topics: Robot & Motion planning. The author has an hindex of 18, co-authored 29 publications receiving 1190 citations. Previous affiliations of Jeffrey A. Delmerico include Microsoft & United States Army Research Laboratory.
Papers
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Proceedings ArticleDOI
A Benchmark Comparison of Monocular Visual-Inertial Odometry Algorithms for Flying Robots
TL;DR: This paper evaluates an array of publicly-available VIO pipelines on different hardware configurations, including several single-board computer systems that are typically found on flying robots, and considers the pose estimation accuracy, per-frame processing time, and CPU and memory load while processing the EuRoC datasets.
Journal ArticleDOI
The current state and future outlook of rescue robotics
Jeffrey A. Delmerico,Stefano Mintchev,Alessandro Giusti,Gromov Boris A,Kamilo Melo,Tomislav Horvat,Cesar Cadena,Marco Hutter,Auke Jan Ijspeert,Dario Floreano,Luca Maria Gambardella,Roland Siegwart,Davide Scaramuzza +12 more
TL;DR: The current state of the art in ground and aerial robots, marine and amphibious systems, and human–robot control interfaces are surveyed and the readiness of these technologies with respect to the needs of first responders and disaster recovery efforts is assessed.
Proceedings ArticleDOI
Vision-based autonomous quadrotor landing on a moving platform
TL;DR: To the best of the knowledge, this is the first demonstration of a fully autonomous quadrotor system capable of landing on a moving target, using only on-board sensing and computing, without relying on any external infrastructure.
Proceedings ArticleDOI
Are We Ready for Autonomous Drone Racing? The UZH-FPV Drone Racing Dataset
TL;DR: The UZH-FPV Drone Racing dataset is introduced, consisting of over 27 sequences, with more than 10 km of flight distance, captured on a first-person-view (FPV) racing quadrotor flown by an expert pilot, providing a dataset that is beyond the capabilities of existing state estimation algorithms.
Proceedings ArticleDOI
An information gain formulation for active volumetric 3D reconstruction
TL;DR: This work proposes and evaluates several formulations to quantify information gain for volumetric reconstruction of an object by a mobile robot equipped with a camera, including visibility likelihood and the likelihood of seeing new parts of the object.