Results 41 to 50 of about 4,275 (207)
Lidar-based scale recovery dense SLAM for UAV navigation [PDF]
, 2022 openImagine of having an autonomous agent (drone, robot, car, ..) that wants to navigate inside an unknown environment. The first question that it needs to answer for accomplish such task is: where Am I?
ANDREOLI, JACOPO
core
Tightly Coupled 3D Lidar Inertial SLAM for Ground Robot [PDF]
, 2023 This paper proposes a robotic state estimation and map construction method. The traditional lidar SLAM methods are affected by sensor measurement noise, which causes the estimated trajectory to drift, especially along the altitude direction caused by ...
Bo Sun +3 more
core +1 more source
VIRAL SLAM: Tightly Coupled Camera-IMU-UWB-Lidar SLAM
CoRR, 2021 In this paper, we propose a tightly-coupled, multi-modal simultaneous localization and mapping (SLAM) framework, integrating an extensive set of sensors: IMU, cameras, multiple lidars, and Ultra-wideband (UWB) range measurements, hence referred to as VIRAL (visual-inertial-ranging-lidar) SLAM.
Thien-Minh Nguyen +4 more
openaire +2 more sources
Visual-LiDAR SLAM Based on Unsupervised Multi-channel Deep Neural Networks [PDF]
, 2022 Recently, deep learning techniques have been applied to solve visual or light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) problems.
Shi, Jin +3 more
core +1 more source
Research on SLAM Algorithm of Mobile Robot Based on the Fusion of 2D LiDAR and Depth Camera
IEEE Access, 2020 This paper proposes a new Simultaneous Localization and Mapping (SLAM) method on the basis of graph-based optimization through the combination of the Light Detection and Ranging (LiDAR), RGB-D camera, encoder and Inertial Measurement Unit (IMU).
Lili Mu +5 more
doaj +1 more source
CamVox: A Low-cost and Accurate Lidar-assited Visual SLAM System [PDF]
, 2021 Combining lidar in camera-based simultaneous localization and mapping (SLAM) is an effective method in improving overall accuracy, especially at outdoor large scale scenes. Recent development of low-cost lidars (e.g.
Yuewen Zhu; Chunran Zheng; Chongjian Yuan; Xu Huang; Xiaoping Hong
core +1 more source
Robust Lidar SLAM Under Adverse Weather [PDF]
, 2023 LiDAR Simultaneous Localization and Mapping (SLAM) technologies, which are the foundational technology of autonomous driving, have attracted large interest recently and been a significant research field. The performance of existing State-Of-The-Art LiDAR
Cheng, Qian
core
Deep Learning-Aided Inertial/Visual/LiDAR Integration for GNSS-Challenging Environments
Sensors, 2023 This research develops an integrated navigation system, which fuses the measurements of the inertial measurement unit (IMU), LiDAR, and monocular camera using an extended Kalman filter (EKF) to provide accurate positioning during prolonged GNSS signal ...
Nader Abdelaziz, Ahmed El-Rabbany
doaj +1 more source
LIDAR-INERTIAL NAVIGATION BASED ON MAP AIDED DISTANCE CONSTRAINT AND FACTOR GRAPH OPTIMIZATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 The simultaneous localization and mapping (SLAM) is one of the well-developed positioning technology that provides high accuracy and reliability positioning for automatic vehicles and robotics applications. Integrating Light Detection and Ranging (LiDAR)
M. Ai +3 more
doaj +1 more source
Differentiable SLAM Helps Deep Learning-based LiDAR Perception Tasks [PDF]
, 2023 We investigate a new paradigm that uses differentiable SLAM architectures in a self-supervised manner to train end-to-end deep learning models in various LiDAR based applications.
Dong, Erqun +4 more
core +1 more source