Research on multi-sensor data fusion algorithm for unmanned vehicles under extreme conditions

Aiming at the problem of insufficient accuracy in Simultaneous Localization and Mapping of vehicle robot using a single sensor in extreme environment scenes, according to the characteristics of the sensors, a method of fusing the data of lidar and inertial sensors is proposed, the vehicle robot syst...

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Bibliographic Details
Published in:Journal of physics. Conference series Vol. 1952; no. 3; pp. 32001 - 32008
Main Author: Zhang, Ruiqi
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.06.2021
Subjects:
Algorithms
Data integration
Extreme environment
Extreme environments
Inertial sensing devices
Kalman filter
Kalman filters
Lidar
Multisensor fusion
Physics
Robots
sensor fusion
Sensors
Unmanned vehicles
ISSN:1742-6588, 1742-6596
Online Access:Get full text
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Summary:Aiming at the problem of insufficient accuracy in Simultaneous Localization and Mapping of vehicle robot using a single sensor in extreme environment scenes, according to the characteristics of the sensors, a method of fusing the data of lidar and inertial sensors is proposed, the vehicle robot system is designed, and the positioning principle of lidar and inertial sensor is elaborated. Two data fusion algorithms, weighted fusion and Kalman filter, are mainly studied, and the experiments prove that the Kalman filter algorithm has higher positioning accuracy.
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1952/3/032001