RSS-LIWOM: Rotating Solid-State LiDAR for Robust LiDAR-Inertial-Wheel Odometry and Mapping

Solid-state LiDAR offers multiple advantages over mechanism mechanical LiDAR, including higher durability, improved coverage ratio, and lower prices. However, solid-state LiDARs typically possess a narrow field of view, making them less suitable for odometry and mapping systems, especially for mobil...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-08, Vol.15 (16), p.4040
Main Authors: Gong, Shunjie, Shi, Chenghao, Zhang, Hui, Lu, Huimin, Zeng, Zhiwen, Chen, Xieyuanli
Format: Article
Language:English
Subjects:
Algorithms
Coders
Deep learning
Design and construction
Indoor environments
Kalman filters
LiDAR
Localization
Mapping
Methods
Multisensor fusion
odometry and mapping
Optical radar
Optimization
Remote sensing
Robots
Robustness
Rotation
Sensors
Servomotors
SLAM
Solid state
urban environment
Visual field
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Summary:Solid-state LiDAR offers multiple advantages over mechanism mechanical LiDAR, including higher durability, improved coverage ratio, and lower prices. However, solid-state LiDARs typically possess a narrow field of view, making them less suitable for odometry and mapping systems, especially for mobile autonomous systems. To address this issue, we propose a novel rotating solid-state LiDAR system that incorporates a servo motor to continuously rotate the solid-state LiDAR, expanding the horizontal field of view to 360°. Additionally, we propose a multi-sensor fusion odometry and mapping algorithm for our developed sensory system that integrates an IMU, wheel encoder, motor encoder and the LiDAR into an iterated Kalman filter to obtain a robust odometry estimation. Through comprehensive experiments, we demonstrate the effectiveness of our proposed approach in both outdoor open environments and narrow indoor environments.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15164040