Sökning: "Iterative Closest Points Algorithm ICP"
Visar resultat 1 - 5 av 8 uppsatser innehållade orden Iterative Closest Points Algorithm ICP.
1. Point Cloud Registration using both Machine Learning and Non-learning Methods : with Data from a Photon-counting LIDAR Sensor
Master-uppsats, Linköpings universitet/DatorseendeSammanfattning : Point Cloud Registration with data measured from a photon-counting LIDAR sensor from a large distance (500 m - 1.5 km) is an expanding field. Data measuredfrom far is sparse and have low detail, which can make the registration processdifficult, and registering this type of data is fairly unexplored. LÄS MER
2. Static Extrinsic Calibration of a Vehicle-Mounted Lidar Using Spherical Targets
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysikSammanfattning : Self-driving cars are steadily becoming a reality by a growing number of driver assistance functions enabled by smart perception sensors. The light detection and ranging (lidar) sensor show great potential for perception tasks due to its precise distance measurements. LÄS MER
3. Real Time Lidar and ICP-Based Odometry in Dynamic Environments
Master-uppsats, Linköpings universitet/ReglerteknikSammanfattning : A robust and highly accurate positioning system is required to transition to fully autonomous vehicles in society. This thesis investigates the potential for lidar sensors to be a part of a localization system, adding redundancy in case of an outage in a global navigation satellite system GNSS. LÄS MER
4. Development of an ICP-based Global Localization System
Master-uppsats, Linköpings universitet/ReglerteknikSammanfattning : The most common way to track the position of a vehicle is by using the Global Navigation Satellite System (GNSS). Unfortunately, there are many scenarios where GNSS is inaccessible or provides low precision, and it can therefore be vulnerable to only rely on GNSS. LÄS MER
5. Relative pose estimation of a plane on an airfield with automotive-class solid-state LiDAR sensors : Enhancing vehicular localization with point cloud registration
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Point cloud registration is a technique to align two sets of points with manifold applications across a range of industries. However, due to a lack of adequate sensing technology, this technique has seldom found applications in the automotive sector up to now. LÄS MER