Simultaneous Localization and Mapping (SLAM) for Autonomous Driving: Concept and Analysis
Remote Sensing, 2023 The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing progress over the last few decades and has generated considerable interest in the autonomous driving community.
Shuran Zheng +4 more
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Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM). [PDF]
Sensors (Basel), 2022 We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant ...
Laal S +4 more
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Visual SLAM algorithms and their application for AR, mapping, localization and wayfinding
Array, 2022 Visual simultaneous localization and mapping (vSLAM) algorithms use device camera to estimate agent's position and reconstruct structures in an unknown environment.
Charalambos Theodorou +3 more
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Drones, 2022 This article presents a survey of simultaneous localization and mapping (SLAM) and data fusion techniques for object detection and environmental scene perception in unmanned aerial vehicles (UAVs). We critically evaluate some current SLAM implementations
Abhishek Gupta, Xavier Fernando
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Mutual information-based hierarchical NBV decision for active semantic visual SLAM under dynamic environments [PDF]
Scientific ReportsActive Simultaneous Localization and Mapping (A-SLAM) technology enables a robot to autonomously plan its movements to build a comprehensive and accurate map of its surroundings.
Zhenyuan Yang +3 more
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Stereo Gaussian Splatting with Adaptive Scene Depth Estimation for Semantic Mapping [PDF]
Journal of ImagingSimultaneous Localization and Mapping (SLAM) is a fundamental capability in robotics and augmented reality. However, achieving accurate geometric reconstruction and consistent semantic understanding in complex environments remains challenging.
Chenhui Fu, Jiangang Lu
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Sensor Technologies and Simultaneous Localization and Mapping (SLAM)
Procedia Computer Science, 2015 AbstractThis paper presents a comprehensive review on sensor modalities currently in used for solving the Simultaneous Localization and Mapping (SLAM) problem. The review focuses on SLAM for mobile robots in a variety of environments. The strengths and weaknesses of acoustic modality sensors such as ultrasonic and sonar sensors, laser range finders ...
Chong, T.J. +5 more
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P-SLAM: Simultaneous Localization and Mapping With Environmental-Structure Prediction [PDF]
IEEE Transactions on Robotics, 2007 Traditionally, simultaneous localization and mapping (SLAM) algorithms solve the localization and mapping problem in explored regions. This paper presents a prediction-based SLAM algorithm (called P-SLAM), which has an environmental-structure predictor to predict the structure inside an unexplored region (i.e., look-ahead mapping).
Y Charlie Hu +2 more
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Three main paradigms of simultaneous localization and mapping (SLAM) problem
Tenth International Conference on Machine Vision (ICMV 2017), 2018 Simultaneous Localization and Mapping (SLAM) is one of the most challenging research areas within computer and machine vision for automated scene commentary and explanation. The SLAM technique has been a developing research area in the robotics context during recent years.
Vandad Imani +2 more
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The Accuracy Comparison of Three Simultaneous Localization and Mapping (SLAM)-Based Indoor Mapping Technologies [PDF]
Sensors, 2018 Juha Hyyppä +2 more
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