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Updated: Jan 19, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
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GNSS/LiDAR-Based Navigation of an Aerial Robot in Sparse Forests.

Antonio C B Chiella1, Henrique N Machado2, Bruno O S Teixeira3

  • 1Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte-MG 31270-901, Brazil. acbchiella@ufmg.br.

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Summary

This study presents a robust autonomous navigation system for aerial robots in forests. It effectively combines sensor data for precise localization and planning for obstacle avoidance, enabling safe flight in challenging environments.

Keywords:
forest flightmotion planningrobust state estimationsensor fusionsurveillance

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Area of Science:

  • Robotics
  • Autonomous Systems
  • Environmental Perception

Background:

  • Autonomous navigation in forests is difficult due to degraded Global Navigation Satellite System (GNSS) signals and numerous obstacles.
  • Detailed pre-mapping of forest environments is often impractical for unmanned vehicles.

Purpose of the Study:

  • To develop a complete autonomous navigation solution for aerial robots in sparse forests.
  • To enable reliable localization and obstacle avoidance in environments with intermittent GNSS availability.

Main Methods:

  • A state estimator fusing GNSS, Attitude and Heading Reference Systems (AHRS), and LiDAR-based odometry using tree trunks for feature matching.
  • A robust adaptive fusion algorithm based on the unscented Kalman filter for state estimation.
  • A motion control strategy integrating a vector field for directional guidance and an optimal probabilistic planner for obstacle avoidance.

Main Results:

  • Demonstrated effective localization by merging diverse sensor inputs (GNSS, AHRS, LiDAR).
  • Successfully implemented LiDAR-based odometry using tree trunks for relative vehicle movement estimation.
  • Validated the integrated motion control strategy for directional movement and obstacle avoidance in a forest setting.

Conclusions:

  • The proposed navigation system effectively addresses the challenges of autonomous aerial robot operation in forest environments.
  • The fusion of GNSS, AHRS, and LiDAR odometry provides robust localization.
  • The integrated motion control ensures safe and directed navigation, as shown in experimental results.