A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.

A beginner-friendly SLAM mini-course with Jupyter notebooks — covering Bayes Filters, Kalman Filters, Particle Filters, and Graph-based SLAM with hands-on Python examples.

QuickMCL - Monte Carlo Localisation for ROS

Project for ROB 550. Implementing SLAM using LIDAR, wheel encoders and IMU on MBot.

This ROS2 package aims to demonstrate how the Particle Filter or Monte Carlo Localization is implemented in a real robot in a simulation world.

C++ implementation of Monte-Carlo Localization

ROS-Noetic-AMCL

demo / examples for tsdf_localization package

This repository implements Monte Carlo Localization (MCL) for VEX V5RC in the standard Vexcode Pro V5 without any external libraries or pluggins; just vanilla C++. With this code and documentation you can enhance position tracking accuracy in the vex game environment.

Monte Carlo Localization using Particle Filtering

Turtlebots playing hockey, my contribution: localization

Robot Localization for autumn heroehscup (Humanoid)

IMPLEMENTAÇÃO DE UM ALGORITMO DE LOCALIZAÇÃO DE ROBÔS MÓVEIS

monte carlo localization - very much indev, debatably over-engineered boilerplate hell, but maybe it'll be good for research at some point

A 2D Monte Carlo Localization (MCL) simulator with a ray-casting LIDAR, written in C++17 and SFML. It demonstrates probabilistic robot localization using particles, sensor models, and resampling. Designed as a learning tool for robotics and C++ simulation projects.

Localization in a static map, planning in a local map.

A MCL simulation implementation in Zig using Raylib

A mobile service robot, capable of localization, mapping and navigating an unknown environment.