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Blitz-SLAM: A semantic SLAM in dynamic environments
Pattern Recognition, 2022Abstract Static environment is a prerequisite for most of visual simultaneous localization and mapping systems. Such a strong assumption limits the practical application of most existing SLAM systems. When moving objects enter the camera’s view field, dynamic matching points will directly interrupt the camera localization, and the noise blocks formed
Yingchun Fan +2 more
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DE‐SLAM: SLAM for highly dynamic environment
Journal of Field Robotics, 2022AbstractSimultaneous localization and mapping (SLAM) is crucial for autonomous mobile robots. Most of the current SLAM systems are based on an assumption: the environment is static. However, the real environment is full of dynamic elements, such as pedestrians or vehicles, as well as changes in illumination and appearance over time.
Zhiwei Xing, Xiaorui Zhu
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ORB-SLAM: A Versatile and Accurate Monocular SLAM System [PDF]
IEEE Transactions on Robotics, 2015 This paper presents ORB-SLAM, a feature-based monocular SLAM system that operates in real time, in small and large, indoor and outdoor environments. The system is robust to severe motion clutter, allows wide baseline loop closing and relocalization, and includes full automatic initialization.
Raúl Mur-Artal +2 more
exaly +5 more sources
2021
SLAM has achieved excellent achievement in the development of the past two decades and it has been extensively developed in robotics communities. The present binocular SLAM is based on the standard binocular camera to obtain images, and they have good positioning accuracy. However, it is necessary to detect and locate objects in the scene.
Mingchi Feng +3 more
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SLAM has achieved excellent achievement in the development of the past two decades and it has been extensively developed in robotics communities. The present binocular SLAM is based on the standard binocular camera to obtain images, and they have good positioning accuracy. However, it is necessary to detect and locate objects in the scene.
Mingchi Feng +3 more
openaire +1 more source
LS-SLAM: SLAM with Lebesgue sampling
2016 American Control Conference (ACC), 2016In the traditional SLAM framework, the state estimate is updated at a fixed frequency. However, such an approach can be inefficient because there is no need to update the state estimate when the deviation between two sequential estimates is within the predefined tolerance bound.
Tao Han +3 more
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A-SLAM: Human in-the-loop Augmented SLAM
2019 International Conference on Robotics and Automation (ICRA), 2019In this work, we are proposing an intuitive Augmented SLAM method (A-SLAM) that allows the user to interact, in real-time, with a robot running SLAM to correct for pose and map errors. We built an AR application that works on HoloLens and allows the operator to view the robot’s map superposed on the physical environment and edit it. Through map editing,
Abbas Sidaoui +3 more
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2008 10th International Conference on Control, Automation, Robotics and Vision, 2008
In this paper, we presented a novel approach for robot Simultaneous Localization and Mapping (SLAM) in an indoor environment. We observed that such an environment is partitioned into rooms and corridors. We thus propose that the robot should compute a map beginning with a conceptual view of its environment rather than a physical view of it.
Mee-Loong Yang, Wai-Kiang Yeap
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In this paper, we presented a novel approach for robot Simultaneous Localization and Mapping (SLAM) in an indoor environment. We observed that such an environment is partitioned into rooms and corridors. We thus propose that the robot should compute a map beginning with a conceptual view of its environment rather than a physical view of it.
Mee-Loong Yang, Wai-Kiang Yeap
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∇SLAM: Dense SLAM meets Automatic Differentiation
2020 IEEE International Conference on Robotics and Automation (ICRA), 2020The question of "representation" is central in the context of dense simultaneous localization and mapping (SLAM). Learning-based approaches have the potential to leverage data or task performance to directly inform the representation. However, blending representation learning approaches with "classical" SLAM systems has remained an open question ...
Krishna Murthy Jatavallabhula +2 more
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2015 12th Conference on Computer and Robot Vision, 2015
This paper demonstrates infrastructure-free orbital Simultaneous Localization and Mapping (SLAM). Individual surface landmarks are tracked through images taken in orbit and the filter receives measurements of these landmarks in the form of bearing angles. The filter then updates the spacecraft's position and velocity as well as landmark locations, thus
Corinne Vassallo +2 more
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This paper demonstrates infrastructure-free orbital Simultaneous Localization and Mapping (SLAM). Individual surface landmarks are tracked through images taken in orbit and the filter receives measurements of these landmarks in the form of bearing angles. The filter then updates the spacecraft's position and velocity as well as landmark locations, thus
Corinne Vassallo +2 more
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DT-SLAM: Deferred Triangulation for Robust SLAM
2014 2nd International Conference on 3D Vision, 2014Obtaining a good baseline between different video frames is one of the key elements in vision-based monocular SLAM systems. However, if the video frames contain only a few 2D feature correspondences with a good baseline, or the camera only rotates without sufficient translation in the beginning, tracking and mapping becomes unstable.
Daniel Herrera C. +4 more
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