Tracking an Object as a Vehicle Using Real-Time Data from a Fixed LIDAR Tower and Dual GPS Sensors
Examensarbete på kandidatnivå
Abstract Autonomous vehicles are used in various fields. They are typically positioned using GPS, but in many cases, GPS does not provide precise and accurate results,especially in proximity to obstacles such as walls or large metal containers in port environments.To overcome this, methods are needed to position a vehicle using real-time data from LIDAR and GPS. The purpose of this thesis is to analyze methods for positioning a vehicle using real-time data from LIDAR and GPS. There is relative freedom in choosing which method we will use. In this study, a unique and new approach is implemented by using a Fixed LIDAR Tower in addition to a single GPS sensor installed in a vehicle. The collected data on the vehicle’s precise location is transmitted to the Control Room at the Shipping Port for further analysis and monitoring. Using the Extended Kalman Filter to combine data from multiple sensors, a new way to track and locate a vehicle is suggested and tested in a simulated environment. Different algorithms are compared and analyzed, mainly emphasizing the main emphasis being on effectiveness, computing efficiency, and applicability. The objective is to build a robust framework for a vehicle tracking system, improve autonomous navigation, and lay the groundwork for later testing and real-world application.
Fixed LIDAR Tower, Dual GPS Sensors,Path planning,collision avoid ance,Localization, Vehicle Location in Real-Time, Shipping Port Control Room. , Fixed LIDAR Tower , Dual GPS Sensors , Path planning , collision avoidance , Vehicle Location in Real-Time , Shipping Port Control Room