TY - GEN
T1 - Research on SLAM System Based on Binocular Vision and IMU Information
AU - Luo, Xiao
AU - Han, Baoling
AU - Luo, Qingsheng
AU - Zhong, Xinliang
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Simultaneous localization and mapping (SLAM) is one of the key technologies in the field of robotics, is the key to autonomous navigation of mobile robots, and is also the core and foundation of autonomous and intelligent mobile robots. The SLAM method which relied information solely on monocular cameras is too dependent on the characteristic information of the surrounding environment. For the lack of the scene texture, the dramatic changes of the illumination and the poor performance of the dynamic scene, and the low frame rate of the visual sensor, it cannot deal with the situation of fast motion. The inertial measurement unit (IMU) can output the acceleration and angular velocity of the sensor itself at a high frame rate, and is not affected by the environment, but with serious drift. To solve this problem, this paper aims to design a SLAM system which combines binocular vision information and IMU information. It can realize robust and precise positioning in unknown environment, and provide corresponding navigation map for navigation.
AB - Simultaneous localization and mapping (SLAM) is one of the key technologies in the field of robotics, is the key to autonomous navigation of mobile robots, and is also the core and foundation of autonomous and intelligent mobile robots. The SLAM method which relied information solely on monocular cameras is too dependent on the characteristic information of the surrounding environment. For the lack of the scene texture, the dramatic changes of the illumination and the poor performance of the dynamic scene, and the low frame rate of the visual sensor, it cannot deal with the situation of fast motion. The inertial measurement unit (IMU) can output the acceleration and angular velocity of the sensor itself at a high frame rate, and is not affected by the environment, but with serious drift. To solve this problem, this paper aims to design a SLAM system which combines binocular vision information and IMU information. It can realize robust and precise positioning in unknown environment, and provide corresponding navigation map for navigation.
KW - Location
KW - Loop detection
KW - Nonlinear optimization
KW - Visual SLAM
UR - http://www.scopus.com/inward/record.url?scp=85097825449&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-63403-2_50
DO - 10.1007/978-3-030-63403-2_50
M3 - Conference contribution
AN - SCOPUS:85097825449
SN - 9783030634025
T3 - Advances in Intelligent Systems and Computing
SP - 557
EP - 567
BT - ICGG 2020 - Proceedings of the 19th International Conference on Geometry and Graphics
A2 - Cheng, Liang-Yee
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th International Conference on Geometry and Graphics, ICGG 2020
Y2 - 18 January 2021 through 22 January 2021
ER -