Essays about: "Visual-Inertial Odometry"

Showing result 1 - 5 of 8 essays containing the words Visual-Inertial Odometry.

  1. 1. Visual-Inertial SLAM Using a Monocular Camera and Detailed Map Data

    University essay from Linköpings universitet/Reglerteknik

    Author : Viktor Ekström; Ludvig Berglund; [2023]
    Keywords : SLAM; localisation; monocular camera; GTSAM; factor graphs; iSAM2;

    Abstract : The most commonly used localisation methods, such as GPS, rely on external signals to generate an estimate of the location. There is a need of systems which are independent of external signals in order to increase the robustness of the localisation capabilities. READ MORE

  3. 2. Rolling shutter in feature-based Visual-SLAM : Robustness through rectification in a wearable and monocular context

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Caspar Norée Palm; [2023]
    Keywords : SLAM; rolling; shutter; rectification; ORB-SLAM3; monocular; camera; compensation; visual; odometry; simultaneous; localization; mapping;

    Abstract : This thesis analyzes the impact of and implements compensation for rolling shutter distortions in the state-of-the-art feature-based visual SLAM system ORB-SLAM3. The compensation method involves rectifying the detected features, and the evaluation was conducted on the "Rolling-Shutter Visual-Inertial Odometry Dataset" from TUM, which comprises of ten sequences recorded with side-by-side synchronized global and rolling shutter cameras in a single room. READ MORE

  4. 3. Robustness of State-of-the-Art Visual Odometry and SLAM Systems

    University essay from KTH/Tillämpad fysik

    Author : Cassandra Mannila; [2023]
    Keywords : Visual-Inertial Odometry; Visual Odometry; SLAM; Motion blur; ORB-SLAM3; DM-VIO; Robustness;

    Abstract : Visual(-Inertial) Odometry (VIO) and Simultaneous Localization and Mapping (SLAM) are hot topics in Computer Vision today. These technologies have various applications, including robotics, autonomous driving, and virtual reality. They may also be valuable in studying human behavior and navigation through head-mounted visual systems. READ MORE

  5. 4. Probabilistic Multi-Modal Data Fusion and Precision Coordination for Autonomous Mobile Systems Navigation : A Predictive and Collaborative Approach to Visual-Inertial Odometry in Distributed Sensor Networks using Edge Nodes

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Isabella Luppi; [2023]
    Keywords : Distributed Sensor Networks; Point Cloud Processing; Bounding Box Fitting; Trajectory Tracking; Distributed Estimation; Predictive Estimation; Edge-Computing; Reti di Sensori Distribuiti; Elaborazione di Nuvole di Punti; Riquadri di Delimitazione; Tracciamento della Traiettoria; Stima Distribuita; Stima Predittiva; Calcolo Distribuito.; Distribuerade Sensornätverk; Bearbetning av Punktmoln; Anpassning av Begränsningsruta; Trajektorieuppföljning; Distribuerad Uppskattning; Prediktiv Uppskattning; Edge-datorbehandling;

    Abstract : This research proposes a novel approach for improving autonomous mobile system navigation in dynamic and potentially occluded environments. The research introduces a tracking framework that combines data from stationary sensing units and on-board sensors, addressing challenges of computational efficiency, reliability, and scalability. READ MORE

  6. 5. Deep Visual Inertial-Aided Feature Extraction Network for Visual Odometry : Deep Neural Network training scheme to fuse visual and inertial information for feature extraction

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Franco Serra; [2022]
    Keywords : Feature extraction network; Visual Odometry; IMU; Neural Network; Pose estimation; Feature extraction; Visuell Odometri; IMU; Neuralt nätverk; Poseuppskattning;

    Abstract : Feature extraction is an essential part of the Visual Odometry problem. In recent years, with the rise of Neural Networks, the problem has shifted from a more classical to a deep learning approach. This thesis presents a fine-tuned feature extraction network trained on pose estimation as a proxy task. READ MORE