Udacity Self-Driving Car Engineer Nanodegree projects.

⚡ The Mobile Robot Programming Toolkit (MRPT)

solution of exercises of the book "probabilistic robotics"

Implementation of "A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application"

An implementation of the Particle Filter using C++ for the purposes of localization.

A flexible, modern, C++ recursive Bayesian estimation library.

ROS package of Depth-Based Bayesian Object Tracking

Kalman filter sanctuary - including continuous-discrete extended Kalman filter. Bring additional filters here for a bigger collection.

Sensor Fusion and Localization related projects of Udacity's Self-driving Car Nanodegree Program:

🚀 SLAM for autonomous planetary rovers with global localization

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.

Custom navigation stack for Turtlebot3. Includes Fast SLAM, EKF SLAM, several path planners, and a model predictive path integral controller.

Self Driving Car Nanodegree Offered By Udacity

Generic Sensor Fusion Package for ROS

C++/CUDA solutions, slides, and resources for Udacity's Intro to Computer Vision (UD810) course.

2D LiDAR scanner simulator with map editor implemented in C++ / ROS

Rcpp bindings for Sequential Monte Carlo

A Particle Filter algorithm which could be used to localize an autonomous system such as a UAV or a self-driving car.

Implemented a C++ particle filter for real-time vehicle localization with only current visual observations and a map.

SIA - C++/Python library for model-based stochastic estimation and optimal control