🔌✨ Welcome to My Electronics & Embedded Systems Project Repository! 🎯🚀 📂 This repository is a treasure trove of exciting projects built using various microcontrollers & embedded systems, including: 🔹 Arduino 🤖 🔹 ESP8266 & ESP32 📶 🔹 Raspberry Pi 🍓💻 🔹 ...and many more! 🔥 🛠️ Whether you're into automation, or 🤖 robotics.

Webots Robot Simulator

Simulation Description Format (SDFormat) parser and description files.

General purpose math library for robot applications.

The open source software platform for creating applications that enable the design and control of automated means of production.

An audio-visual library supports processing audio and video files, a graphics library can load a variety 3D mesh file formats into a generic in-memory representation, and the core library of Gazebo Common contains functionality that spans Base64 encoding/decoding to thread pools.

Homebrew tap for osrf simulation software

The universal industrial complex projecting and control system.

Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research.

A Python-based lightweight robot simulator designed for navigation, control, and reinforcement learning

Open source robotics simulator. The latest version of Gazebo.

C++ library designed to provide an abstraction for different rendering engines. It offers unified APIs for creating 3D graphics applications.

Integration between ROS (1 and 2) and Gazebo simulation

Model and simulate multibody systems in Julia

ESP32-powered modular snake robot with 8+ motion gaits, Bluepad32 gamepad control, ToF sensors, and autonomous navigation. Arduino-based locomotion system with 10 DOF.

Robotodo NVIDIA Omniverse simulation engine

Provides numerous sensor models designed to generate realistic data from simulation environments.

Abstract physics interface designed to support simulation and rapid development of robot applications.

myGym enables fast prototyping of RL in the area of robotic manipulation and navigation.You can train different robots, in several environments on various tasks. There is automatic evaluation and benchmark tool. From version 2.1 there is support for multi-step tasks, multi-reward training and multi-network architectures.

Research testbed comparing Linear PID, Sliding Mode Control (SMC), and Linear Model Predictive Control (LMPC) for aggressive quadrotor trajectory tracking. Validated in PyBullet with RMSE analysis.