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Monocular Visual SLAM Based on a Cooperative UAV-Target System.

Juan-Carlos Trujillo1, Rodrigo Munguia1, Sarquis Urzua1

  • 1Department of Computer Science, CUCEI, University of Guadalajara, Guadalajara 44430, Mexico.

Sensors (Basel, Switzerland)
|June 26, 2020
PubMed
Summary
This summary is machine-generated.

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This study introduces a monocular SLAM system for Unmanned Aerial Vehicles (UAVs) to track cooperative targets in GPS-denied environments. The approach enhances state estimation and flight formation control using altimeter data and target-based depth estimation.

Area of Science:

  • Robotics
  • Computer Vision
  • Control Systems

Background:

  • Autonomous Unmanned Aerial Vehicles (UAVs) require self-location and environmental perception.
  • Global Positioning System (GPS) is unreliable in indoor or cluttered environments.
  • Monocular Simultaneous Localization and Mapping (SLAM) offers an alternative for GPS-denied navigation.

Purpose of the Study:

  • To develop a monocular SLAM approach for cooperative UAV-Target systems in GPS-denied environments.
  • To address state estimation for UAV and target (position, velocity) and map (landmarks).
  • To enable stable flight formation control between a UAV and a cooperative target.

Main Methods:

  • Implemented a monocular SLAM system utilizing onboard camera data.
  • Integrated altimeter measurements to enhance observability.
Keywords:
cooperative targetflight formation controlmonocular SLAMobservabilitystate estimationunmanned aerial vehicle

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  • Developed a novel technique for estimating visual landmark depth using the cooperative target.
  • Designed a control system for stable flight formation, validated with Lyapunov theory.

    • Main Results:

    • The proposed system effectively estimates the states of the UAV, target, and map.
    • Incorporating altitude measurements improved system observability.
    • The novel depth estimation technique leverages the cooperative target's information.
    • Experimental and simulation results demonstrate good performance of the proposed scheme.

    Conclusions:

    • The monocular SLAM approach provides a viable solution for cooperative UAV navigation in GPS-denied scenarios.
    • The integration of altimeter data and target-based depth estimation enhances system robustness.
    • The developed control system ensures stable flight formation, crucial for cooperative missions.