Loop Closure Detection Method Based on Similarity Differences between Image Blocks [PDF]
Sensors, 2023 Variations with respect to perspective, lighting, weather, and interference from dynamic objects may all have an impact on the accuracy of the entire system during autonomous positioning and during the navigation of mobile visual simultaneous ...
Yizhe Huang +5 more
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A Semantic Topology Graph to Detect Re-Localization and Loop Closure of the Visual Simultaneous Localization and Mapping System in a Dynamic Environment [PDF]
Sensors, 2023 Simultaneous localization and mapping (SLAM) plays a crucial role in the field of intelligent mobile robots. However, the traditional Visual SLAM (VSLAM) framework is based on strong assumptions about static environments, which are not applicable to ...
Yang Wang +5 more
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A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph Optimization
Remote Sensing, 2021 LiDAR (light detection and ranging), as an active sensor, is investigated in the simultaneous localization and mapping (SLAM) system. Typically, a LiDAR SLAM system consists of front-end odometry and back-end optimization modules.
Shoubin Chen +4 more
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TS-LCD: Two-Stage Loop-Closure Detection Based on Heterogeneous Data Fusion [PDF]
SensorsLoop-closure detection plays a pivotal role in simultaneous localization and mapping (SLAM). It serves to minimize cumulative errors and ensure the overall consistency of the generated map.
Fangdi Jiang +6 more
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Loop Closure Detection Using Local 3D Deep Descriptors [PDF]
IEEE Robotics and Automation Letters, 2022 We present a simple yet effective method to address loop closure detection in simultaneous localisation and mapping using local 3D deep descriptors (L3Ds). L3Ds are emerging compact representations of patches extracted from point clouds that are learnt from data using a deep learning algorithm.
Youjie Zhou, Yiming Wang, Fabio Poiesi
exaly +4 more sources
SVG-Loop: Semantic–Visual–Geometric Information-Based Loop Closure Detection
Remote Sensing, 2021 Loop closure detection is an important component of visual simultaneous localization and mapping (SLAM). However, most existing loop closure detection methods are vulnerable to complex environments and use limited information from images. As higher-level
Zhian Yuan +4 more
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Role of Deep Learning in Loop Closure Detection for Visual and Lidar SLAM: A Survey [PDF]
Sensors, 2021 Gon-Woo Kim
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Sequential Loop Closure Based Adaptive Output Feedback
IEEE Access, 2017 This paper presents a new, systematic method of synthesizing an output feedback adaptive controller for a class of uncertain, non-square multi-input/multi-output systems. The control design process consists of first designing an inner-loop controller for
Daniel P. Wiese +4 more
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VCC: Vertical Feature and Circle Combined Descriptor for 3D Place Recognition [PDF]
SensorsLoop closure detection remains a critical challenge in LiDAR-based SLAM, particularly for achieving robust place recognition in environments with rotational and translational variations.
Wenguang Li +5 more
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Place Recognition with Memorable and Stable Cues for Loop Closure of Visual SLAM Systems
Robotics, 2022 Visual Place Recognition (VPR) is a fundamental yet challenging task in Visual Simultaneous Localization and Mapping (V-SLAM) problems. The VPR works as a subsystem of the V-SLAM.
Rafiqul Islam, Habibullah Habibullah
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