A neural network based landing method for an unmanned aerial vehicle with soft landing gears

Cai Luo, Weikang Zhao, Zhenpeng Du, Leijian Yu

Research output: Contribution to journalArticle

Abstract

This paper presents the design, implementation, and testing of a soft landing gear together with a neural network-based control method for replicating avian landing behavior on non-flat surfaces. With full consideration of unmanned aerial vehicles and landing gear requirements, a quadrotor helicopter, comprised of one flying unit and one landing assistance unit, is employed. Considering the touchdown speed and posture, a novel design of a soft mechanism for non-flat surfaces is proposed, in order to absorb the remaining landing impact. The framework of the control strategy is designed based on a derived dynamic model. A neural network-based backstepping controller is applied to achieve the desired trajectory. The simulation and outdoor testing results attest to the effectiveness and reliability of the proposed control method.
LanguageEnglish
Article number2976
Number of pages16
JournalApplied Sciences
Volume9
Issue number15
DOIs
Publication statusPublished - 25 Jul 2019

Fingerprint

landing gear
Landing gear (aircraft)
soft landing
pilotless aircraft
landing
Unmanned aerial vehicles (UAV)
Landing
Neural networks
touchdown
posture
Backstepping
helicopters
Testing
Helicopters
dynamic models
Dynamic models
controllers
Trajectories
trajectories
flight

Keywords

  • unmanned aerial vehicle
  • neural network
  • soft landing gear
  • aerospace
  • design

Cite this

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title = "A neural network based landing method for an unmanned aerial vehicle with soft landing gears",
abstract = "This paper presents the design, implementation, and testing of a soft landing gear together with a neural network-based control method for replicating avian landing behavior on non-flat surfaces. With full consideration of unmanned aerial vehicles and landing gear requirements, a quadrotor helicopter, comprised of one flying unit and one landing assistance unit, is employed. Considering the touchdown speed and posture, a novel design of a soft mechanism for non-flat surfaces is proposed, in order to absorb the remaining landing impact. The framework of the control strategy is designed based on a derived dynamic model. A neural network-based backstepping controller is applied to achieve the desired trajectory. The simulation and outdoor testing results attest to the effectiveness and reliability of the proposed control method.",
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A neural network based landing method for an unmanned aerial vehicle with soft landing gears. / Luo, Cai; Zhao, Weikang; Du, Zhenpeng; Yu, Leijian.

In: Applied Sciences, Vol. 9, No. 15, 2976, 25.07.2019.

Research output: Contribution to journalArticle

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