• 185 Citations
  • 8 h-Index
20012019
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Fingerprint Dive into the research topics where David Gaylor is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 2 Similar Profiles
Navigation Engineering & Materials Science
Orbits Engineering & Materials Science
Spacecraft Engineering & Materials Science
navigation Physics & Astronomy
spacecraft Physics & Astronomy
Global positioning system Engineering & Materials Science
Space flight Engineering & Materials Science
Satellites Engineering & Materials Science

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Research Output 2001 2019

  • 185 Citations
  • 8 h-Index
  • 18 Conference contribution
  • 3 Article
  • 1 Chapter

Safe rendezvous trajectory design for the restore-l mission

Vavrina, M. A., Skelton, C. E., Deweese, K. D., Naasz, B. J., Gaylor, D. E. & D’souza, C., Jan 1 2019, Spaceflight Mechanics 2019. Topputo, F., Sinclair, A. J., Wilkins, M. P. & Zanetti, R. (eds.). Univelt Inc., p. 3649-3668 20 p. AAS 19-410. (Advances in the Astronautical Sciences; vol. 168).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

rendezvous trajectories
Landsat 7
navigation
trajectory
Trajectories

Simultaneous localization and mapping for satellite rendezvous and proximity operations using random finite sets

Schlenker, L., Moretto, M., Gaylor, D. & Linares, R., Jan 1 2019, Spaceflight Mechanics 2019. Topputo, F., Sinclair, A. J., Wilkins, M. P. & Zanetti, R. (eds.). Univelt Inc., p. 3401-3419 19 p. AAS 19-282. (Advances in the Astronautical Sciences; vol. 168).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

orbital rendezvous
Spacecraft
proximity
navigation
spacecraft

A deep learning approach for optical autonomous planetary relative terrain navigation

Campbell, T., Furfaro, R., Linares, R. & Gaylor, D., 2017, Spaceflight Mechanics 2017. Univelt Inc., Vol. 160. p. 3293-3302 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

navigation
learning
Navigation
Neural networks
autonomous navigation

Development of a tool for analyzing orbits around asteroids

Niedling, J., Gaylor, D., Hallmann, M. & Foerstner, R., 2016, Spaceflight Mechanics 2016. Univelt Inc., Vol. 158. p. 3535-3553 19 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Asteroids
asteroids
asteroid
Orbits
orbits
machine learning
Learning systems
sensor
sensors
Sensors