001492681 001__ 1492681
001492681 005__ 20240614003157.0
001492681 02470 $$a10.1109/ACCESS.2024.3359908$$2DOI
001492681 037__ $$aIR
001492681 041__ $$aeng
001492681 245__ $$aTightly-Coupled SLAM Integrating LiDAR and INS for Unmanned Vehicle Navigation in Campus Environments
001492681 269__ $$a2024-02-19
001492681 520__ $$aSimultaneous Localization and Mapping (SLAM) is one of the key issues for mobile robots
to achieve true autonomy. The implementations of SLAM could rely on a variety of sensors. Among many
types of them, the laser-based SLAM approach is widely used owing to its high accuracy, even in poor
lighting conditions. However, when in structure-less environments, laser modules will fail due to a lack
of sufficient geometric features. Besides, motion estimation by moving lidar has the problem of distortion
since range measurements are received continuously. To solve these problems, we propose a tightly-coupled
SLAM integrating LiDAR and an integrated navigation system (INS) for unmanned vehicle navigation in
campus environments. On the basis of feature extraction, a constraint equation for inter-frame point cloud
features is constructed, and the pose solution results of the INS are added as a priori data for inter-frame point
cloud registration. The Levenberg-Marquardt nonlinear least square method is used to solve the constraint
equation to obtain inter-frame pose relationships. Map matching and loop closure detection methods are used
to optimize the odometer, and the optimal pose information is obtained. The proposed SLAM algorithm
is evaluated by comparing with the classic open-source laser SLAM algorithms on the campus dataset.
Experimental results demonstrate that our proposed algorithm has certain advantages in estimating the
trajectory error of the unmanned vehicle and has higher mapping performance.
001492681 536__ $$oKey Research and Development Support Program of Chengdu Science and Technology Bureau of Sichuan Province under Grant 2022-YF05-01128-SN
001492681 536__ $$o Research Fund of the Chengdu University of Information Technology under Grant KYTZ202108
001492681 536__ $$oOpening Project of Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province under Grant WRXT2021-002
001492681 536__ $$oOpening Project of International Joint Research Center for Robotics and Intelligence System of Sichuan Province under Grant JQZN2021-001
001492681 536__ $$oSichuan Science and Technology Planning Project under Grant 2021YFH0069, under Grant 2023YFG0178, and under Grant 2023YFG0045
001492681 536__ $$o Science and Technology Innovation Ability Improvement Plan of Chengdu University of Information Technology under Grant KYTD202228
001492681 6531_ $$aSLAM
001492681 6531_ $$amobile robot
001492681 6531_ $$alocalization and navigation
001492681 6531_ $$amulti-sensor data fusion
001492681 6531_ $$aliDAR and INS
001492681 6531_ $$ahigh-precision point cloud map
001492681 7001_ $$aZhang, Linshuai$$uChengdu University of Traditional Chinese Medicine
001492681 7001_ $$aWang, Qian$$uChengdu University of Information Technology
001492681 7001_ $$aGu, Shuoxin$$uChengdu University of Information Technology
001492681 7001_ $$aJiang, Tao$$uChengdu University of Traditional Chinese Medicine
001492681 7001_ $$aJiang, Shiqi$$uChengdu University of Information Technology
001492681 7001_ $$aLiu, Jiajia$$uChengdu University of Information Technology
001492681 7001_ $$aLuo, Shuang$$uChengdu University of Information Technology
001492681 7001_ $$aYan, Gongjun$$uUniversity of Southern Indiana
001492681 773__ $$tIEEE Access
001492681 8564_ $$99f9d5f63-651d-4df7-acff-ee49b5b30766$$s2877154$$uhttps://library.usi.edu/record/1492681/files/Tightly-Coupled_SLAM_Integrating_LiDAR_and_INS_for_Unmanned_Vehicle_Navigation_in_Campus_Environments%20%281%29.pdf
001492681 909CO $$ooai:library.usi.edu:1492681$$pGLOBAL_SET
001492681 980__ $$aMANUSCRIPT