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Peterson J, Chaudhry H, Abdelatty K, et al. Online Aerial Terrain Mapping for Ground Robot Navigation. Sensors (Basel). 2018;18(2)doi: 10.3390/s18020630.
Peterson, J., Chaudhry, H., Abdelatty, K., Bird, J., & Kochersberger, K. (2018). Online Aerial Terrain Mapping for Ground Robot Navigation. Sensors (Basel, Switzerland), 18(2), . https://doi.org/10.3390/s18020630
Peterson, John, et al. "Online Aerial Terrain Mapping for Ground Robot Navigation." Sensors (Basel, Switzerland) vol. 18,2 (2018). doi: https://doi.org/10.3390/s18020630
Peterson J, Chaudhry H, Abdelatty K, Bird J, Kochersberger K. Online Aerial Terrain Mapping for Ground Robot Navigation. Sensors (Basel). 2018 Feb 20;18(2). doi: 10.3390/s18020630. PMID: 29461496; PMCID: PMC5855888.
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Sensors (Basel). 2018 Feb 20;18(2). doi: 10.3390/s18020630.

Online Aerial Terrain Mapping for Ground Robot Navigation.

Sensors (Basel, Switzerland)

John Peterson, Haseeb Chaudhry, Karim Abdelatty, John Bird, Kevin Kochersberger

Affiliations

  1. Virginia Tech Unmanned Systems Laboratory, Blacksburg, VA 24060, USA. [email protected].
  2. Virginia Tech Unmanned Systems Laboratory, Blacksburg, VA 24060, USA. [email protected].
  3. Virginia Tech Unmanned Systems Laboratory, Blacksburg, VA 24060, USA. [email protected].
  4. Virginia Tech Unmanned Systems Laboratory, Blacksburg, VA 24060, USA. [email protected].
  5. Virginia Tech Unmanned Systems Laboratory, Blacksburg, VA 24060, USA. [email protected].

PMID: 29461496 PMCID: PMC5855888 DOI: 10.3390/s18020630

Abstract

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle's overhead view to inform the ground vehicle's path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles.

Keywords: air–ground cooperation; multi-robot coordination; unmanned aircraft

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