Essays about: "mobile LiDAR"

Showing result 1 - 5 of 14 essays containing the words mobile LiDAR.

  1. 1. Robust Multi-Modal Fusion for 3D Object Detection : Using multiple sensors of different types to robustly detect, classify, and position objects in three dimensions.

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

    Author : Viktor Kårefjärd; [2023]
    Keywords : Computer Vision; 3D Object Detection; Multi-Modal Fusion; Deep Learning; Datorseenden; 3D-objektdetektion; Multimodal fusion; Djupinlärning;

    Abstract : The computer vision task of 3D object detection is fundamentally necessary for autonomous driving perception systems. These vehicles typically feature a multitude of sensors, such as cameras, radars, and light detection and ranging sensors. READ MORE

  3. 2. 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

  4. 3. Unsupervised Domain Adaptation for 3D Object Detection Using Adversarial Adaptation : Learning Transferable LiDAR Features for a Delivery Robot

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

    Author : Mattias Hansson; [2023]
    Keywords : Unsupervised Domain Adaptation; 3D Object Detection; Mobile Robotics; Adversarial Adaptation; Computer Vision; Oövervakad Domänanpassning; 3D Objektigenkänning; Mobila Robotar; Motspelaranpassning; Datorseende;

    Abstract : 3D object detection is the task of detecting the full 3D pose of objects relative to an autonomous platform. It is an important perception system that can be used to plan actions according to the behavior of other dynamic objects in an environment. READ MORE

  5. 4. Robotics Approach in Mobile Laser Scanning : Generation of Georeferenced Point-based Forest Models

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

    Author : Tamas Faitli; [2023]
    Keywords : mobile laser scanning; rotating lidar; slam; real-time positioning; georeferencing; state estimation; lidar odometry; point-based forest model; forest harvester; forestry; mobil laserskanning; roterande lidar; slam; realtidspositionering; georeferens; tillståndsuppskattning; lidarodometri; punktbaserad skogsmodell; skogsskördare; skogsbruk;

    Abstract : A mobile laser scanning (MLS) system equipped with a lidar, inertial navigation system and satellite positioning can be used to reconstruct georeferenced point-based models of the surveyed environments. Ideal reconstruction requires accurate trajectories that are challenging to obtain in forests. READ MORE

  6. 5. Research and Application of 6D Pose Estimation for Mobile 3D Cameras

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

    Author : Qian Ruichao; [2022]
    Keywords : 6 Degree-of-Freedom DoF ; pose estimation; deep learning; Light Detection and Ranging LiDAR ; structure light; TrueDepth; 6 frihetsgrader DoF ; poseringsuppskattning; djupinlärning; ljusdetektion och avstånd LiDAR ; strukturljus; TrueDepth;

    Abstract : This work addresses the deep-learning-based 6 Degree-of-Freedom (DoF) pose estimation utilizing 3D cameras on an iPhone 13 Pro. The task of pose estimation is to estimate the spatial rotation and translation of an object given its 2D or 3D images. READ MORE