Results 11 to 20 of about 1,309 (133)
Benchmarking Pedestrian Odometry: The Brown Pedestrian Odometry Dataset (BPOD)
2022 International Conference on 3D Vision (3DV), 2022 We present the Brown Pedestrian Odometry Dataset (BPOD) for benchmarking visual odometry algorithms in head-mounted pedestrian settings. This dataset was captured using synchronized global and rolling shutter stereo cameras in 12 diverse indoor and outdoor locations on Brown University's campus.
David Charatan +2 more
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Robocentric Visual-Inertial Odometry [PDF]
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018 In this paper, we propose a novel robocentric formulation of the visual–inertial navigation system (VINS) within a sliding-window filtering framework and design an efficient, lightweight, robocentric visual–inertial odometry (R-VIO) algorithm for consistent motion tracking even in challenging environments using only a monocular camera and a six-axis ...
Zheng Huai, Guoquan Huang 0001
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Social Odometry: Imitation Based Odometry in Collective Robotics
International Journal of Advanced Robotic Systems, 2009 The improvement of odometry systems in collective robotics remains an important challenge for several applications. Social odometry is an online social dynamics which confers the robots the possibility to learn from the others. Robots neither share any movement constraint nor access to centralized information.
Gutiérrez Martín, Álvaro +4 more
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A Unified Formulation for Visual Odometry [PDF]
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019 Monocular Odometry systems can be broadly categorized as being either Direct, Indirect, or a hybrid of both. While Indirect systems process an alternative image representation to compute geometric residuals, Direct methods process the image pixels directly to generate photometric residuals.
Georges Younes 0001 +2 more
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Machines, 2023 In a vehicle, wheel speed sensors and inertial measurement units (IMUs) are present onboard, and their raw data can be used for localization estimation. Both wheel sensors and IMUs encounter challenges such as bias and measurement noise, which accumulate
Norbert Markó +3 more
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Bias compensation in visual odometry [PDF]
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012 Empirical evidence shows that error growth in visual odometry is biased. A projective bias model is developed and its parameters are estimated offline from trajectories encompassing loops. The model is used online to compensate for bias and thereby significantly reduces error growth.
Gijs Dubbelman +2 more
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The Archimede Rover: A Comparison between Simulations and Experiments
Robotics, 2023 In this paper, we propose an in-depth evaluation of the performance of the Archimede rover while traversing rough terrain with loose soil. In order to better analyze this, the reality gap is evaluated when simulating the behavior with an open-source ...
Matteo Caruso +4 more
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IEEE Robotics & Automation Magazine, 2011 Visual odometry (VO) is the process of estimating the egomotion of an agent (e.g., vehicle, human, and robot) using only the input of a single or If multiple cameras attached to it. Application domains include robotics, wearable computing, augmented reality, and automotive. The term VO was coined in 2004 by Nister in his landmark paper.
Davide Scaramuzza 0001 +1 more
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Direct Line Guidance Odometry [PDF]
2018 IEEE International Conference on Robotics and Automation (ICRA), 2018 Modern visual odometry algorithms utilize sparse point-based features for tracking due to their low computational cost. Current state-of-the-art methods are split between indirect methods that process features extracted from the image, and indirect methods that deal directly on pixel intensities.
Shijie Li 0006 +5 more
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