Design and Verification of Observability-Driven Autonomous Vehicle Exploration Using LiDAR SLAM

This paper explores the research topic of enhancing the reliability of unmanned mobile exploration using LiDAR SLAM. Specifically, it proposes a technique to analyze waypoints where 3D LiDAR SLAM can be smoothly performed in potential exploration areas and points where there is a risk of divergence...

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Bibliographic Details
Published in:Aerospace 2024-01, Vol.11 (2), p.120
Main Authors: Kim, Donggyun, Lee, Byungjin, Sung, Sangkyung
Format: Article
Language:English
Subjects:
Algorithms
condition number
Driverless cars
Evaluation
exploration
Gazebo
Lidar
observability
Optical radar
Path planning
Remote sensing
Robots
Sensors
Simultaneous localization and mapping
SLAM
unmanned vehicle
Unmanned vehicles
Waypoints
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Summary:This paper explores the research topic of enhancing the reliability of unmanned mobile exploration using LiDAR SLAM. Specifically, it proposes a technique to analyze waypoints where 3D LiDAR SLAM can be smoothly performed in potential exploration areas and points where there is a risk of divergence in navigation estimation. The goal is to improve exploration performance by presenting a method that secures these candidate regions. The analysis employs a 3D geometric observability matrix and its condition number to discriminate waypoints. Subsequently, the discriminated values are applied to path planning, resulting in the derivation of a final destination path connecting waypoints with a satisfactory SLAM position and attitude estimation performance. To validate the proposed technique, performance analysis was initially conducted using the Gazebo simulator. Additionally, experiments were performed with an autonomous unmanned vehicle in a real-world environment.
ISSN:2226-4310
2226-4310
DOI:10.3390/aerospace11020120