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Visual-Based SLAM Configurations for Cooperative Multi-UAV Systems with a Lead Agent: An Observability-Based

Juan-Carlos Trujillo1, Rodrigo Munguia2, Edmundo Guerra3

  • 1Department of Computer Science, CUCEI, University of Guadalajara, Guadalajara 44430, Mexico. juancarlos_max@hotmail.com.

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Summary
This summary is machine-generated.

This study introduces cooperative visual-simultaneous localization and mapping (SLAM) for multi-unmanned aerial vehicle (UAV) systems following a lead agent. The method robustly estimates the positions of UAVs and the lead agent, even in GPS-denied environments.

Keywords:
aerial robotscooperative SLAMobservabilitystate estimation

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Area of Science:

  • Robotics
  • Computer Vision
  • Control Systems

Background:

  • Cooperative Simultaneous Localization and Mapping (SLAM) is crucial for multi-unmanned aerial vehicle (UAV) systems.
  • Estimating the states of individual UAVs and a dynamic lead agent is a fundamental challenge.

Purpose of the Study:

  • To address cooperative visual-based SLAM for multi-UAV systems with a lead agent.
  • To develop robust state estimation for aerial robots and their lead agent.

Main Methods:

  • Investigated three system configurations using nonlinear observability analysis.
  • Proposed a high-level control scheme for formation control relative to the lead agent.

Main Results:

  • Theoretical results and extensive computer simulations validated the proposed approach.
  • Demonstrated robust performance in GPS-challenging environments.

Conclusions:

  • The cooperative visual-SLAM method provides accurate position estimation for UAVs and lead agents.
  • The approach is effective in various conditions, enhancing multi-UAV system capabilities.