Robotics Project 2, Politecnico di Milano, A. Y. 2021/22, Computer Science and Engineering

Submission for Project 3 of Udacity Robotics Nanodegree: Implement Adaptive Monte Carlo Localisation (AMCL) C++ algorithm to localise a robot in a pre-generated map.

Final project of the Udacity's Robotics Software Engineer Nanodegree.

下一代的Mineacrft启动器

Simple AMCL localization package.

Turtlebot navigates its environment using AMCL, gmapping and other custom packages. Robotics Software Engineer Nanodegree @udacity

This project aims to simulate a mobile robot used to transport sensible material

Localizing Robot inside a map using ROS amcl.

Utilize ROS AMCL package to accurately localize a mobile robot inside a map in the Gazebo simulation environments.

Perfomance tests for ROS MCL implementations

On this Udacity project we simulate a full home service robot capable of navigating to pick up and deliver virtual objects.

ROS AMCL node that includes an additional detector node that processes visual landmarks to improve robot localization in indoor environments

Particle filter (Monte Carlo Localisation or MCL) in Python

Autonomous Robot ROS Stack

Project 3: Where Am I (AMCL)

Udacity Home Service Robot Project

Udacity Robotics Software Engineer Nanodegree Project 3 - Where Am I?

ROS implementation of the iRobot Create 2

Udacity Robotics Software Engineer Nanodegree Program - Project 3