Sökning: "Vehicle Cloud"

Visar resultat 1 - 5 av 64 uppsatser innehållade orden Vehicle Cloud.

  1. 1. Assessing the Efficiency of COLMAP, DROID-SLAM, and NeRF-SLAM in 3D Road Scene Reconstruction

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marcus Ascard; Farjam Movahedi; [2023]
    Nyckelord :3D reconstruction; Visual SLAM; Pose evaluation; Point cloud evaluation; Road scenes; Technology and Engineering;

    Sammanfattning : 3D reconstruction is a field in computer vision which has evolved rapidly as a result of the recent advancements in deep learning. As 3D reconstruction pipelines now can run in real-time, this has opened up new possibilities for teams developing Advanced Driver Assistance Systems (ADAS), which rely on the camera system of the vehicle to enhance the safety and driving experience. LÄS MER

  3. 2. Performance metrics and velocity influence for point cloud registration in autonomous vehicles

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Óscar Poveda Ruiz; [2023]
    Nyckelord :autonomous vehicle; localization; registration; metrics; error; classification; estimation; autonomt fordon; lokalisering; registrering; mätvärden; fel; klassificering; uppskattning;

    Sammanfattning : Autonomous vehicles are currently under study and one of the critical parts is the localization of the vehicle in the environment. Different localization methods have been studied over the years, such as the GPS sensor, commonly fused with other sensors such as the IMU. LÄS MER

  4. 3. LiDAR Perception in a Virtual Environment Using Deep Learning : A comparative study of state-of-the-art 3D object detection models on synthetic data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Samuel Skoog; [2023]
    Nyckelord :Object Detection; LiDAR; CARLA; Deep Learning; Autonomous Vehicles; Objektdetektering; LiDAR; CARLA; Djupinlärning; Autonoma fordon;

    Sammanfattning : Perceiving the environment is a crucial aspect of autonomous vehicles. To plan the route, the autonomous vehicle needs to be able to detect objects such as cars and pedestrians. This is possible through 3D object detection. However, labeling this type of data is time-consuming. LÄS MER

  5. 4. Domain Adaptation Of Front View Synthetic Point Clouds Using GANs For Autonomous Driving

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Friedemann Kleinsteuber; [2023]
    Nyckelord :LiDAR; Domain Adaptation; GAN; CycleGAN; Simulation; LiDAR; Domänadaption; GAN; CycleGAN; Simulation;

    Sammanfattning : The perception of the environment is one of the main enablers of Autonomous Driving and is driven by Cameras, RADAR, and LiDAR sensors. Deep Learning algorithms used in perception need a vast amount of labeled, high-quality data which is costly to obtain for LiDAR sensors. LÄS MER

  7. 5. Application development of 3D LiDAR sensor for display computers

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :Oskar Ekstrand; [2023]
    Nyckelord :LiDAR; 3D sensor; display computer; application; high-resolution 3D map; visualize real time data; CPU load; Voxel grid filter; Point Cloud Library; Qt QML; C ; Linux; LiDAR; 3D sensor; fordons dator; applikation; högupplöst 3D-karta; visualisera realtidsdata; processorlast; Voxel grid filter; Point Cloud Library; Qt QML; C ; Linux;

    Sammanfattning : A highly accurate sensor for measuring distances, used for creating high-resolution 3D maps of the environment, utilize “Light Detection And Ranging” (LiDAR) technology. This degree project aims to investigate the implementation of 3D LiDAR sensors into off-highway vehicle display computers, called CCpilots. LÄS MER