Results 81 to 90 of about 200,418 (165)
IaNDT-SLAM: intensity-augmented NDT for robust LiDAR-inertial SLAM in unstructured environments
Geo-spatial Information ScienceLight detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) has proven effective for robust perception in challenging environments.
Xin Yang +6 more
doaj +1 more source
Applied Sciences, 2019 The method of simultaneous localization and mapping (SLAM) using a light detection and ranging (LiDAR) sensor is commonly adopted for robot navigation. However, consumer robots are price sensitive and often have to use low-cost sensors.
Guolai Jiang +5 more
doaj +1 more source
A Tightly Coupled LiDAR-Inertial SLAM for Perceptually Degraded Scenes
, 2022 Realizing robust six degrees of freedom (6DOF) state estimation and high-performance simultaneous localization and mapping (SLAM) for perceptually degraded scenes (such as underground tunnels, corridors, and roadways) is a challenge in robotics. To solve
Chuanwei Wang +4 more
core +1 more source
EnergiesCurrent substation inspection robots mainly use Lidar as a sensor for localization and map building. However, laser SLAM has the problem of localization error in scenes with similar and missing environmental structural features, and environmental maps ...
Yicen Liu, Songhai Fan
doaj +1 more source
Scale Estimation of Monocular Camera SLAM using a 2D Lidar [PDF]
, 2023 SLAM using a monocular camera has the problem that scale cannot be uniquely estimated, and scale drift occurs. This study uses 2D Lidar scan data to improve scale drift and enable scale estimation.
高橋 大陸
core
Development of SLAM for UGV Based on Stabilized 3D LiDAR
Simultaneous Localization and Mapping (SLAM) is a critical component for autonomous off-road vehicles, where Global Navigation Satellite System (GNSS) signals may be unreliable and the environment is unstructured.
Johnson, Lucy +3 more
core +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
Smart ROUV advances for enhanced navigation in the Suez Canal
Scientific ReportsRemotely Operated Underwater Vehicles (ROUVs) are increasingly important for high-resolution surveying of narrow shipping lanes. This paper presents 3Clifs, a LiDAR- and AI-enhanced ROUV designed for near-real-time topographic mapping and navigation ...
Khaled Oqda +11 more
doaj +1 more source
Doppler-SLAM: Doppler-Aided Radar-Inertial and LiDAR-Inertial Simultaneous Localization and Mapping
Simultaneous localization and mapping is a critical capability for autonomous systems. Traditional SLAM approaches often rely on visual or LiDAR sensors and face significant challenges in adverse conditions such as low light or featureless environments ...
Wang, Dong +5 more
core +1 more source
Applied SciencesSLAM (Simultaneous Localization and Mapping), primarily relying on camera or LiDAR (Light Detection and Ranging) sensors, plays a crucial role in robotics for localization and environmental reconstruction.
Yu-Lin Zhao +2 more
doaj +1 more source