2019 Chinese Control and Decision Conference (CCDC) 2019
DOI: 10.1109/ccdc.2019.8832695
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Cited by 11 publications
(4 citation statements)
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“…Over the past decade, deep learning has made tremendous strides towards the ultimate goal of achieving full driving autonomy [1]. Self-driving vehicles deploy a suite of different sensors such as RADAR, GPS, IMU, LIDAR, cameras or their combination for various tasks such as object detection, classification, localization and navigation [2], [3], [4], [5], [6]. Among them, vision based sensors (Cameras, Lidar etc.)…”
Section: Introductionmentioning
confidence: 99%
“…Over the past decade, deep learning has made tremendous strides towards the ultimate goal of achieving full driving autonomy [1]. Self-driving vehicles deploy a suite of different sensors such as RADAR, GPS, IMU, LIDAR, cameras or their combination for various tasks such as object detection, classification, localization and navigation [2], [3], [4], [5], [6]. Among them, vision based sensors (Cameras, Lidar etc.)…”
Section: Introductionmentioning
confidence: 99%
“…Inertial sensors, also known as inertial measurement units (IMUs), are commonly rigidly attached to an object to help track or estimate position and orientation information [ 10 ]. IMU sensors have been applied to a greater number of application areas, including pose estimation for robotics, autonomous vehicles [ 11 ], and human motion tracking [ 1 ] and visualization [ 12 ]. However, although IMU sensors are accurate over short periods, they suffer from occlusions and drift over longer periods [ 13 ], and hence, are commonly combined with other sensors.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, in view of the low vertical resolution of VLP-16 and the possible failure of LiDAR-SLAM, this paper implemented a GNSS/IMU/ODO/LiDAR-SLAM integrated navigation system based on the LeGO-LOAM (Lightweight and ground-optimized lidar odometry and mapping) [ 5 ] feature matching method and the solution [ 19 ] for road environments. Odometer information is usually converted to the forward speed for assistance [ 24 , 25 ]. Although this method is convenient, it is difficult to obtain the accurate speed of the auxiliary moment because the original measurement information of the odometer is mileage.…”
Section: Introductionmentioning
confidence: 99%