Results 21 to 30 of about 162,677 (314)
Post-integration based point-line feature visual SLAM in low-texture environments [PDF]
Scientific ReportsTo address the issues of weak robustness and low accuracy of traditional SLAM data processing algorithms in weak texture environments such as low light and low contrast, this paper first studies and improves the data feature extraction method, optimizing
Yanli Liu +3 more
doaj +2 more sources
Visual Loop Closure Detection Through Deep Graph Consensus
2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Visual loop closure detection traditionally relies on place recognition methods to retrieve candidate loops that are validated using computationally expensive RANSAC-based geometric verification.
Martin Buchner +6 more
semanticscholar +3 more sources
LiDAR Iris for Loop-Closure Detection [PDF]
2020 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
2022 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
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Loop Closure Detection for Mobile Robot based on Multidimensional Image Feature Fusion
Machines, 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]
2019 IEEE 15th International Conference on Control and Automation (ICCA), 2019 IEEE International Conference on Control and Automation (ICCA ...
Wang, Han +3 more
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Loop closure detection using depth images [PDF]
2013 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]
Jisuanji 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]
2019 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
Advanced 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