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SpaceDrones Labeled Training Images and Results
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posted on 2022-03-01, 14:20 authored by Marco Peterson, Minzhen DuMinzhen Du, Bryant Springle, Nadhir CherfaouiLabeled RGB image data of both real world and synthetic environments of orbital;/space platforms for the purposes of supervised machine learning training to enable autonomous robotic tasking.
Funding
Commonwealth Center for Innovation in Autonomous Systems (C2IAS0)
History
Publisher
University Libraries, Virginia TechLanguage
- English
Location
Blacksburg, VAUsage metrics
Categories
- Aerospace engineering not elsewhere classified
- Digital processor architectures
- Other information and computing sciences not elsewhere classified
- Autonomous vehicle systems
- Control engineering, mechatronics and robotics not elsewhere classified
- Mechanical engineering not elsewhere classified
- Satellite, space vehicle and missile design and testing
- Software engineering not elsewhere classified
Keywords
Machine LearningNeural Networks methodDronesRobotics systemsaerospace applicationAssembly PatternsOrbital fibroblasts secretecomputer vision systemsSpaceDronesIn-Space AssemblyOn-orbit servicingAerospace EngineeringComputer EngineeringAutonomous VehiclesControl Systems, Robotics and AutomationMechanical EngineeringSatellite, Space Vehicle and Missile Design and TestingSoftware Engineering