Results 21 to 30 of about 162,676 (316)

LiDAR Iris for Loop-Closure Detection [PDF]

open access: yes2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
In this paper, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for fast and accurate loop-closure detection. A binary signature image can be obtained for each point cloud after several LoG-Gabor filtering and thresholding operations on the LiDAR-Iris image representation.
Wang, Ying   +5 more
openaire   +3 more sources

AirLoop: Lifelong Loop Closure Detection

open access: yes2022 International Conference on Robotics and Automation (ICRA), 2022
Loop closure detection is an important building block that ensures the accuracy and robustness of simultaneous localization and mapping (SLAM) systems. Due to their generalization ability, CNN-based approaches have received increasing attention. Although they normally benefit from training on datasets that are diverse and reflective of the environments,
Gao, Dasong   +2 more
openaire   +2 more sources

Loop Closure Detection for Mobile Robot based on Multidimensional Image Feature Fusion

open access: yesMachines, 2022
Loop closure detection is a crucial part of VSLAM. However, the traditional loop closure detection algorithms are difficult to adapt to complex and changeable scenes.
Jinming Li   +4 more
doaj   +1 more source

Fast Loop Closure Detection via Binary Content [PDF]

open access: yes2019 IEEE 15th International Conference on Control and Automation (ICCA), 2019
IEEE International Conference on Control and Automation (ICCA ...
Wang, Han   +3 more
openaire   +3 more sources

Loop closure detection using depth images [PDF]

open access: yes2013 European Conference on Mobile Robots, 2013
We investigate the question whether loop closure detection using depth images is feasible using currently available depth features. For this reason, we collected a benchmark dataset consisting of a total number of 15 logfiles with several loops in various environments, implemented a modular and easily extensible loop closure detector and used this to ...
Sebastian A. Scherer   +2 more
openaire   +1 more source

Fast Closed Loop Detection Method Based on Simplification Convolutional Neural Network [PDF]

open access: yesJisuanji gongcheng, 2018
Loop closure detection methods based on deep learning can achieve good detection performance in complicate illumination environment.But the dimension of extracted scene feature is too high to achieve the real-time detection requirement for closed loop ...
HE Yuanlie,CHEN Jiateng,ZENG Bi
doaj   +1 more source

Loop Closure Detection in Closed Environments [PDF]

open access: yes2019 European Conference on Mobile Robots (ECMR), 2019
Low cost robots, such as vacuum cleaners or lawn mowers employ simplistic and often random navigation policies. Although a large number of sophisticated mapping and planning approaches exist, they require additional sensors like LIDAR sensors, cameras or time of flight sensors.
Rottmann, Nils   +3 more
openaire   +2 more sources

A Real‐Time and Fast LiDAR–IMU–GNSS SLAM System with Point Cloud Semantic Graph Descriptor Loop‐Closure Detection

open access: yesAdvanced Intelligent Systems, 2023
Herein, a real‐time, fast, tightly coupled simultaneous localization and mapping (SLAM) system is proposed. The deep neural network is used to segment the point cloud semantically to construct the point cloud semantic map descriptor, and the global ...
Yingzhong Tian   +7 more
doaj   +1 more source

A Robust and Efficient Loop Closure Detection Approach for Hybrid Ground/Aerial Vehicles

open access: yesDrones, 2023
Frequent and dramatic viewpoint changes make loop closure detection of hybrid ground/aerial vehicles extremely challenging. To address this issue, we present a robust and efficient loop closure detection approach based on the state-of-the-art ...
Yutong Wang   +3 more
doaj   +1 more source

Loop Closure Detection Based on Differentiable Manifold

open access: yesMobile Information Systems, 2022
Loop closure detection is an important part of SLAM (simultaneous location and mapping), which can effectively reduce the cumulative error of the system after long period of exploration. The existing loop closure detection methods are mainly to evenly distribute the accumulated error in the robot trajectory, but the motion error of the actual robot is ...
Tianzhen Dong   +5 more
openaire   +1 more source

Home - About - Disclaimer - Privacy