Results 101 to 110 of about 14,971 (201)

Real-Time Detection of Non-Stationary Objects Using Intensity Data in Automotive LiDAR SLAM. [PDF]

Sensors (Basel), 2021
Nowak T, Ćwian K, Skrzypczyński P.
europepmc   +1 more source

Benchmarking and Comparing Popular Visual SLAM Algorithms

, 2018
This paper contains the performance analysis and benchmarking of two popular visual SLAM Algorithms: RGBD-SLAM and RTABMap. The dataset used for the analysis is the TUM RGBD Dataset from the Computer Vision Group at TUM.
Kasar, Amey
core  

Large-Scale LiDAR SLAM with Factor Graph Optimization on High-Level Geometric Features. [PDF]

Sensors (Basel), 2021
Ćwian K, Nowicki MR, Wietrzykowski J, Skrzypczyński P.   +3 more
europepmc   +1 more source

End-to-End Navigation in Unknown Environments using Neural Networks

, 2017
We investigate how a neural network can learn perception actions loops for navigation in unknown environments. Specifically, we consider how to learn to navigate in environments populated with cul-de-sacs that represent convex local minima that the robot
Atanasov, Nikolay, Karydis, Konstantinos, Khan, Arbaaz, Kumar, Vijay, Lee, Daniel D., Zhang, Clark   +5 more
core  

Role of Deep Learning in Loop Closure Detection for Visual and Lidar SLAM: A Survey. [PDF]

Sensors (Basel), 2021
Arshad S, Kim GW.
europepmc   +1 more source

GPS‐Denied LiDAR‐Based SLAM—A Survey

IET Cyber-systems and Robotics
In recent years, significant advancements have been made in enabling intelligent unmanned agents to achieve autonomous navigation and positioning within large‐scale indoor or underground environments.
Haolong Jiang, Yikun Cheng, Weichen Dai, Wenbin Wan, Qinyao Liu, Fanxin Wang   +5 more
doaj   +1 more source

Robust Lidar SLAM Under Adverse Weather

, 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 SLAM systems has been proven to produce accurate odometry estimation on autonomous driving datasets.
openaire   +1 more source

PSMD-SLAM: Panoptic Segmentation-Aided Multi-Sensor Fusion Simultaneous Localization and Mapping in Dynamic Scenes

Applied Sciences
Multi-sensor fusion is pivotal in augmenting the robustness and precision of simultaneous localization and mapping (SLAM) systems. The LiDAR–visual–inertial approach has been empirically shown to adeptly amalgamate the benefits of these sensors for SLAM ...
Chengqun Song, Bo Zeng, Jun Cheng, Fuxiang Wu, Fusheng Hao   +4 more
doaj   +1 more source

ROLO‐SLAM: Rotation‐Optimized LiDAR‐Only SLAM in Uneven Terrain With Ground Vehicle

Journal of Field Robotics
ABSTRACTLiDAR‐based SLAM is recognized as one effective method to offer localization guidance in rough environments. However, off‐the‐shelf LiDAR‐based SLAM methods suffer from significant pose estimation drifts, particularly components relevant to the vertical direction, when passing to uneven terrains.
Yinchuan Wang, Bin Ren, Xiang Zhang, Pengyu Wang, Chaoqun Wang, Rui Song, Yibin Li, Max Q.‐H. Meng   +7 more
openaire   +2 more sources

Research on 3D LiDAR Outdoor SLAM Algorithm Based on LiDAR/IMU Tight Coupling

Scientific Reports
Abstract Aiming at the problems of easy loss of GPS positioning signals in outdoor environments and inaccurate map construction and position drift of traditional SLAM algorithms in outdoor scenes, this paper proposes a 3D LiDAR and inertial guidance tightly coupled SLAM algorithm.
Darong Zhu, Qi Wang, Fangbin Wang, Xue Gong   +3 more
openaire   +3 more sources