The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2024
Session ID : 1A1-F01
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LiDAR SLAM-Based Autonomous Obstacle Avoidance Method for Aerial Drones In GNSS-denied Environments
*Masashi IZUMITAKohji TOMITAAkiya KAMIMURA
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Abstract

This study addresses the challenge of autonomous drone flight in environments where GNSS is unavailable, using only onboard sensors like LiDAR and IMU. Focusing on obstacle avoidance without external sensors, we employ LiDAR-based SLAM for real-time 3D mapping and localization, enabling stable flight in diverse settings such as indoor spaces and densely built areas. Our method innovates by mapping environments on-the-fly and applying an extended artificial potential method for navigation, avoiding the common pitfalls of local minima. Simulation results demonstrate the drone's ability to autonomously reach target locations, underlining the potential of LiDAR SLAM for enhancing drone autonomy in GNSS-denied areas. This research lays the groundwork for future advancements in drone technology, promising wider application and efficiency in logistical operations and beyond.

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© 2024 The Japan Society of Mechanical Engineers
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