The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Fast, autonomous flight in GPS‐denied and cluttered environments
Open accessAbstract
One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design and software architecture of our proposed solution and showcase how all the distinct components can be integrated to enable smooth robot operation. We provide critical insight on hardware and software component selection and development and present results from extensive experimental testing in real‐world warehouse environments. Experimental testing reveals that our proposed solution can deliver fast and robust aerial robot autonomous navigation in cluttered, GPS‐denied environments.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2463671 · Cited by 6,778
Parallel Tracking and Mapping for Small AR Workspaces
Klein, G., & Murray, D. (2007) · 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2007.4538852 · Cited by 4,346
Cited by
Learning high-speed flight in the wild
Loquercio, A., Kaufmann, E., Ranftl, R., Müller, M., Koltun, V., & Scaramuzza, D. (2021) · Science Robotics · doi:10.1126/scirobotics.abg5810 · Cited by 375
Self-citationThe current state and future outlook of rescue robotics
Delmerico, J., Mintchev, S., Giusti, A., Gromov, B., Melo, K., Horvat, T., Cadena, C., Hutter, M., Ijspeert, A., Floreano, D., et al. (2019) · Journal of Field Robotics · doi:10.1002/rob.21887 · Cited by 371
Self-citationA Review of GNSS-Independent UAV Navigation Techniques
Gyagenda, N., Hatilima, J. V., Roth, H., & Zhmud, V. (2022) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2022.104069 · Cited by 190
Metadata
- Authors
- Mohta, K., Watterson, M., Mulgaonkar, Y., Liu, S., Qu, C., Makineni, A., Saulnier, K., Sun, K., Zhu, A., Delmerico, J., Karydis, K., Atanasov, N., Loianno, G., Scaramuzza, D., Daniilidis, K., Taylor, C. J., & Kumar, V.
- Venue
- Journal of Field Robotics
- Publisher
- Wiley
- Published
- 2017-12-15
- Volume
- 35
- Issue
- 1
- Pages
- 101-120
- ISSN
- 1556-4959 (ISSN-L)
- 1556-4967
- OpenAlex
- W2771926486
- Cited by
- 200
- References
- 2
- FWCI
- 6.51
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
