This repository contains C++ code for implementation of Particle Filter to localize a vehicle kidnapped in a closed environment. This task was implemented to partially fulfill Term-II goals of Udacity's self driving car nanodegree program.
Implement SLAM, a robust method for tracking an object over time and mapping out its surrounding environment using elements of probability, motion models, linear algerbra.
Exercises based on the CV Nanodegree of Robot Localisation and implementations based on SLAM. Contains the techniques and filters in context to the same from scratch
Project for Artificial intelligence course @ Poznan University of Technology. The goal of the project was to localize robot using reinforcement learning
Particle Filter implementation : implement a particle filter and combine it with a real map to localize an object. Particle filter uses data and a map to determine the precise location of an object such as a robot or a vehicle.