This project implements a particle filter to localize a vehicle in a map

Particle filter (Monte Carlo localization) used to estimate the position of an autonomous car regarding a map.

particle filter localization

Extendable Particle Filter

Udacity Self Driving Engineer Nanodegree - Term 2 - Project 3 - Kidnapped Vehicle

Use image to create an interactive particle image

c++ implementation of 2D particle filter

Deep Recurrent Learning for Bayesian State Estimation of Autonomous Six Degree-of-Freedom Optical Lunar Lander

Udacity Robotics Software Engineer Nanodegree

Project #6 of the Self-Driving Car Engineer Nanodegree Program: Kidnapped Vehicle

Localization (Kidnapped Vehicle) Project for Self-Driving Car ND using C++

Self-driving Car Nano-degree. Term 2: Localization. Project 3: Particle Filter

Locate a Kidnapped car by using a particle filter to identify map landmarks

Implemented a particle filter in order to accuractly localize a vehicle using sensor measurements, an initial noisy GPS reading, and a map of the region.

Build a particle filter in c++ to localize a vehicle in a map given that map and some initial localization information , observation and control data.

the project of CarND-Kidnapped-Vehicle

Built a localizer to figure out where we are in a map.

Implementation of Particle Filter algorithm for localization of a self driving car

Udaccity Self Driving Nanodegree Project 7