Open AccessDesign of Intelligent Robot Platform based on Multi-sensor Fusion
Author(s) -
Ya Dajin,
Xiaochun Liu,
Yue Li,
Junyan Chen,
Huang Rongcun,
Lan Lin
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1606/1/012017
Subject(s) - computer science , inertial measurement unit , sensor fusion , real time computing , lidar , mobile robot navigation , mobile robot , scheme (mathematics) , robot , motion planning , encoder , computer vision , artificial intelligence , robot control , remote sensing , geography , mathematical analysis , mathematics , operating system
The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system.