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RGB-Based Visual-Inertial Odometry via Knowledge Distillation from Self-Supervised Depth Estimation with Foundation Models. [PDF]
Sensors (Basel)Song J, Lee SJ.
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PhenoRob-P: An autonomous robotic system for high-throughput phenotyping of potted plants. [PDF]
Plant PhenomicsShao Y +6 more
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Linear RGB-D SLAM for Structured Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021We propose a new linear RGB-D simultaneous localization and mapping (SLAM) formulation by utilizing planar features of the structured environments. The key idea is to understand a given structured scene and exploit its structural regularities such as the Manhattan world.
Kyungdon Joo +4 more
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2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012
Recently RGB-D sensors have become very popular in the area of Simultaneous Localisation and Mapping (SLAM). The major advantage of these sensors is that they provide a rich source of 3D information at relatively low cost. Unfortunately, these sensors in their current forms only have a range accuracy of up to 4 metres.
Gibson Hu +4 more
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Recently RGB-D sensors have become very popular in the area of Simultaneous Localisation and Mapping (SLAM). The major advantage of these sensors is that they provide a rich source of 3D information at relatively low cost. Unfortunately, these sensors in their current forms only have a range accuracy of up to 4 metres.
Gibson Hu +4 more
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Linear RGB-D SLAM for Atlanta World
2020 IEEE International Conference on Robotics and Automation (ICRA), 2020We present a new linear method for RGB-D based simultaneous localization and mapping (SLAM). Compared to existing techniques relying on the Manhattan world assumption defined by three orthogonal directions, our approach is designed for the more general scenario of the Atlanta world. It consists of a vertical direction and a set of horizontal directions
Kyungdon Joo +4 more
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BAD SLAM: Bundle Adjusted Direct RGB-D SLAM
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019A key component of Simultaneous Localization and Mapping (SLAM) systems is the joint optimization of the estimated 3D map and camera trajectory. Bundle adjustment (BA) is the gold standard for this. Due to the large number of variables in dense RGB-D SLAM, previous work has focused on approximating BA.
Thomas Schöps +2 more
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Object Subtraction Planar RGB-D SLAM
2016 XIII Latin American Robotics Symposium and IV Brazilian Robotics Symposium (LARS/SBR), 2016When using RGB-D SLAM algorithms, a robot often considers dynamic and static objects during the 3D mapping step. To address this problem, this paper aims to present an approach in planar RGB-D SLAM, here called Object Subtraction SLAM (OS-SLAM), using only low-cost RGB-D sensors.
Leonardo Angelo V. de Souto +1 more
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Robust and Efficient RGB-D SLAM in Dynamic Environments
IEEE Transactions on Multimedia, 2021Simultaneous localization and mapping (SLAM) using an RGB-D camera is a key enabling technique for many augmented reality (AR) applications. However, most existing RGB-D SLAM methods could fail in dynamic scenarios due to non-trivial pose estimation errors arising from moving objects.
Xin Yang 0008 +5 more
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Accelerated DNA-SLAM for RGB-D images
Proceedings of the 2018 International Conference on Image and Graphics Processing, 2018In the highly active research field of Simultaneous Localization And Mapping (SLAM), RGB-D images have been a major interest to use. Real-time SLAM for RGB-D images is of great importance since dense methods using all the depth and intensity values showed superior performance in the past.
Mina Ameli +4 more
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