awesome-repositories.com
Blog
MCP
awesome-repositories.com

Descubre los mejores repositorios open-source con nuestra búsqueda potenciada por IA.

ExplorarBúsquedas curadasAlternativas open-sourceSoftware autohospedableBlogMapa del sitio
ProyectoServidor MCPAcerca deCómo clasificamosPrensa
Aviso legalPrivacidadTérminos
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

192 repositorios

Awesome GitHub RepositoriesEmbedded Systems And Robotics

Focuses on autonomous control, sensor data processing, and specialized mechanical movement systems.

Explore 192 awesome GitHub repositories matching hardware & iot · Embedded Systems And Robotics. Refine with filters or upvote what's useful.

Awesome Embedded Systems And Robotics GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • developer-y/cs-video-coursesAvatar de Developer-Y

    Developer-Y/cs-video-courses

    81,816Ver en GitHub↗

    This project is a community-driven educational repository that serves as a comprehensive directory of university-level computer science video lectures. It provides a structured learning path for students and professionals, aggregating high-quality academic resources to facilitate self-paced study across a wide range of technical disciplines. The repository distinguishes itself through a collaborative maintenance model, utilizing version control workflows to allow contributors to expand and update the collection. Content is organized within a single, version-controlled document that leverages

    Lists academic video courses covering the theoretical and practical aspects of robotics and control systems.

    algorithmsbioinformaticscomputational-biology
    Ver en GitHub↗81,816
  • commaai/openpilotAvatar de commaai

    commaai/openpilot

    61,375Ver en GitHub↗

    Openpilot es un sistema de asistencia al conductor de código abierto que se integra con las unidades de control del vehículo para proporcionar dirección, aceleración y frenado automatizados. Funciona como un middleware de robótica automotriz, utilizando un entorno de tiempo de ejecución especializado para procesar datos de sensores y ejecutar comandos de control en tiempo real que gestionan la dinámica del vehículo. La plataforma se distingue por una interfaz agnóstica al hardware que traduce comandos de conducción estandarizados a los protocolos propietarios requeridos por una amplia gama de marcas y modelos de vehículos. Emplea planificación de rutas basada en redes neuronales para predecir trayectorias a partir de datos visuales e históricos, mientras que un bucle de control determinista asegura ajustes de alta frecuencia para la estabilidad del vehículo. Para mantener la seguridad operativa, el sistema incorpora un proceso de vigilancia independiente que monitoriza el rendimiento y activa la desconexión inmediata al detectar anomalías. La arquitectura del software se basa en la fusión de sensores en tiempo real para sincronizar las entradas de cámara y radar en una representación ambiental unificada. Los componentes del sistema se comunican a través de un bus basado en mensajes para facilitar el intercambio de datos de baja latencia entre sensores y actuadores, respaldado por una capa de traducción modular que permite la integración con diversos protocolos de comunicación automotriz.

    Processes raw sensor inputs to issue precise steering, acceleration, and braking commands within a vehicle's native control environment.

    Pythonadvanced-driver-assistance-systemsdriver-assistance-systemsrobotics
    Ver en GitHub↗61,375
  • vsouza/awesome-iosAvatar de vsouza

    vsouza/awesome-ios

    52,496Ver en GitHub↗

    This project is a community-driven directory of software resources, libraries, and tools designed to support iOS application development. It serves as a centralized reference point for developers, organizing a vast ecosystem of third-party components into a searchable, structured index to facilitate discovery and project integration. The repository distinguishes itself through its collaborative curation model, which aggregates disparate utilities into a single, maintainable catalog. By leveraging a flat-file documentation structure, it provides a clear overview of the tools available for nati

    Reads data from hardware sensors to detect device movement and orientation changes.

    Swiftapple-swiftarkitawesome
    Ver en GitHub↗52,496
  • google-research/google-researchAvatar de google-research

    google-research/google-research

    38,139Ver en GitHub↗

    This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed

    Combines natural language understanding with physical robot control to execute complex tasks in real-world environments.

    Jupyter Notebookaimachine-learningresearch
    Ver en GitHub↗38,139
  • pbatard/rufusAvatar de pbatard

    pbatard/rufus

    36,498Ver en GitHub↗

    Rufus is a disk imaging tool designed to create bootable USB drives by writing disk images directly to removable storage media. It functions as a standalone utility that formats drives and prepares installation media for operating systems, hardware deployment, and embedded system flashing. The application distinguishes itself through direct-access disk input and output, which bypasses high-level file system abstractions to perform low-level sector-based write operations. It utilizes specialized stream mapping to translate file system structures from disk images onto physical media, ensuring b

    Writes specialized disk images to removable storage to boot and configure single-board computers.

    Cbiosbootbootable-drives
    Ver en GitHub↗36,498
  • atsushisakai/pythonroboticsAvatar de AtsushiSakai

    AtsushiSakai/PythonRobotics

    29,772Ver en GitHub↗

    PythonRobotics es una colección completa de algoritmos de robótica modulares y simulaciones educativas diseñadas para la navegación autónoma, estimación de estados y control de movimiento. El proyecto proporciona una biblioteca de implementaciones independientes para planificación de rutas, localización, mapeo y cinemática, sirviendo como recurso para que investigadores y estudiantes experimenten con teorías robóticas fundamentales y avanzadas. El proyecto se distingue por un diseño centrado en algoritmos donde cada módulo funciona como un script aislado, permitiendo pruebas independientes y una demostración pedagógica clara. Cada implementación está explícitamente mapeada a literatura académica o libros de texto fundamentales de robótica, asegurando que los modelos matemáticos y las estrategias de control sigan siendo verificables y precisos. Los usuarios pueden ejecutar estos escenarios dentro de un entorno de simulación desacoplado que mantiene su propio estado interno y bucles de control, sin requerir dependencias externas. La superficie de capacidades cubre una amplia gama de dominios robóticos, incluyendo navegación aérea, locomoción bípeda y control de brazos multiarticulados. Cuenta con kits de herramientas extensos para fusión de sensores probabilísticos, mapeo ambiental y seguimiento de trayectorias, todo impulsado por computación numérica de alto rendimiento. Las animaciones geométricas en tiempo real y las estimaciones de estado se renderizan directamente a partir de datos de simulación utilizando bibliotecas de trazado estándar.

    Provides a comprehensive library of fundamental algorithms for autonomous robotic systems.

    Pythonalgorithmanimationautonomous-driving
    Ver en GitHub↗29,772
  • genesis-embodied-ai/genesisAvatar de Genesis-Embodied-AI

    Genesis-Embodied-AI/Genesis

    29,362Ver en GitHub↗

    Genesis is an embodied AI simulation platform and parallelized robotics simulator designed for training general-purpose robotic agents. It integrates a physics engine for robotics that calculates collisions and movements for rigid bodies, soft tissues, and fluids, alongside a photorealistic 3D rendering engine. The platform features a domain randomization framework to vary environment parameters across parallel simulations, aiding in sim-to-real transfer. It supports the integration of real-world captured light fields and Gaussian splatting to provide photorealistic backgrounds within simulat

    Provides comprehensive tools for robotic system automation, including kinematics and joint state control.

    Python
    Ver en GitHub↗29,362
  • emilk/eguiAvatar de emilk

    emilk/egui

    29,409Ver en GitHub↗

    This library is an immediate mode graphical user interface toolkit that reconstructs the entire interface every frame. By executing procedural code within a high-frequency loop that matches the display refresh rate, it allows developers to define interactive elements and state updates directly. The framework utilizes a multi-pass rendering approach to resolve layout dependencies, ensuring that widget sizes and positions are calculated accurately before final placement to prevent visual jitter. The project functions as a cross-platform graphics toolkit, providing a portable rendering layer tha

    Provides efficient graphical dashboards for hardware devices with minimal dependencies.

    Rusteguigame-developmentgamedev
    Ver en GitHub↗29,409
  • genesis-embodied-ai/genesis-worldAvatar de Genesis-Embodied-AI

    Genesis-Embodied-AI/genesis-world

    29,351Ver en GitHub↗

    Genesis World is an embodied AI simulation platform designed for training robotic agents through physics-based interactions. It centers on a multi-physics simulation engine that integrates rigid body, particle, and finite element method dynamics, supported by a parallel simulation kernel compiler that translates Python functions into optimized GPU and CPU kernels. The platform features a photorealistic robot renderer that utilizes path-tracing and Gaussian Splatting to generate synthetic training data. It includes a domain randomization framework to vary lighting and physical parameters acros

    Manages autonomous agent behavior using kinematics solvers, joint controllers, and specialized hardware interfaces.

    Python
    Ver en GitHub↗29,351
  • apolloauto/apolloAvatar de ApolloAuto

    ApolloAuto/apollo

    26,676Ver en GitHub↗

    Apollo es un stack de software integral diseñado para el desarrollo de vehículos autónomos, proporcionando los componentes necesarios para la percepción, planificación y control. Funciona como un middleware de robótica de alto rendimiento, utilizando un bus de datos de publicación-suscripción para facilitar la comunicación de baja latencia entre módulos distribuidos y sensores de hardware. La plataforma integra datos de cámaras, lidar y radar a través de un framework de fusión de sensores para generar un modelo ambiental en tiempo real para la navegación. El sistema cuenta con un framework de tiempo de ejecución basado en componentes que gestiona la programación de tareas y la asignación de recursos, respaldado por una capa de abstracción de hardware que desacopla la lógica de conducción de configuraciones específicas de vehículos. Para garantizar un comportamiento consistente durante las pruebas, incluye un motor de reproducción determinista para flujos de datos de sensores y admite simulación hardware-in-the-loop. La plataforma también emplea programación de grafos acíclicos dirigidos y transporte de memoria compartida de copia cero para optimizar el flujo de datos y la eficiencia computacional en sistemas robóticos complejos. El software proporciona una interfaz de control de vehículo estandarizada para traducir las decisiones de navegación en comandos mecánicos. Hay documentación extensa disponible, incluyendo instrucciones de instalación, guías de integración de hardware y una serie de manuales de inicio rápido para varias versiones de la plataforma.

    Validates algorithms by connecting software modules to simulated or physical vehicle control systems.

    C++apolloautonomous-drivingautonomous-vehicles
    Ver en GitHub↗26,676
  • arendst/tasmotaAvatar de arendst

    arendst/Tasmota

    24,502Ver en GitHub↗

    Tasmota is a universal firmware platform for ESP8266 and ESP32 microcontrollers, designed to provide local control and management of smart home hardware. It functions as an event-driven automation controller that replaces proprietary factory firmware, allowing users to manage relays, sensors, and lighting systems without relying on external cloud services. The system is built on a modular driver architecture that enables dynamic hardware configuration and peripheral support through a web-based management interface. The platform distinguishes itself through a template-driven hardware mapping s

    Adjusts raw sensor data using offsets and scaling to ensure accurate reporting for analog and digital inputs.

    Carduinoautomationesp32
    Ver en GitHub↗24,502
  • radareorg/radare2Avatar de radareorg

    radareorg/radare2

    23,120Ver en GitHub↗

    Radare2 is a comprehensive framework for reverse engineering and analyzing compiled software. It provides a command-line environment designed for disassembling, debugging, and patching binary executables across a wide range of processor architectures and operating systems. The system distinguishes itself through a modular, plugin-based architecture that supports cross-platform analysis and automated workflows. It utilizes memory-mapped file access to enable efficient structural inspection and modification of binaries without requiring full file loads. By lifting machine instructions into a un

    Simulates the behavior of binary code in a controlled environment to analyze logic without executing the file on the host system.

    Cbinary-analysisccommandline
    Ver en GitHub↗23,120
  • huggingface/lerobotAvatar de huggingface

    huggingface/lerobot

    21,687Ver en GitHub↗

    This project is a comprehensive research platform designed for the end-to-end lifecycle of robotic learning. It provides a modular framework for training neural network policies—specifically through imitation and reinforcement learning—and deploying them onto physical robotic hardware. By offering a unified interface for hardware abstraction, the platform decouples high-level control logic from the specific sensors and actuators of diverse robotic systems. The framework distinguishes itself through a standardized approach to data and policy management. It utilizes a consistent schema for reco

    Provides a comprehensive research platform for the end-to-end lifecycle of robotic learning.

    Python
    Ver en GitHub↗21,687
  • lima-vm/limaAvatar de lima-vm

    lima-vm/lima

    21,320Ver en GitHub↗

    Lima is a virtualization engine designed to provision and manage lightweight Linux, macOS, and FreeBSD virtual machines. It functions as a comprehensive virtual machine manager that leverages native hypervisors and system emulation to provide isolated environments for container development, cross-architecture testing, and secure sandboxing. The project distinguishes itself through its template-driven provisioning system, which allows users to define and automate environment configurations via local files or remote URL schemes. It integrates deeply with host systems by providing automated file

    The project uses native hardware translation layers to execute foreign architecture binaries within virtual machines with higher performance than standard emulation.

    Gocontainerdmacosqemu
    Ver en GitHub↗21,320
  • johncoates/aerialAvatar de JohnCoates

    JohnCoates/Aerial

    20,980Ver en GitHub↗

    Aerial is a macOS screensaver application and background manager that replaces static images with a rotating series of high-resolution aerial cinema shots. It functions as an Apple TV video streamer, fetching and displaying official aerial screensavers originally designed for Apple TV to be used as dynamic backgrounds on a Mac. The project integrates Apple TV content to enable desktop wallpaper customization and dynamic screensaver management. This allows the system to stream high-definition aerial views from remote sources to serve as a living background or an automated screensaver when the

    Streams high-definition aerial cinema shots from Apple servers to use as dynamic backgrounds.

    Swift
    Ver en GitHub↗20,980
  • rlabbe/kalman-and-bayesian-filters-in-pythonAvatar de rlabbe

    rlabbe/Kalman-and-Bayesian-Filters-in-Python

    19,050Ver en GitHub↗

    Este proyecto es un recurso educativo y un kit de herramientas para implementar estimación bayesiana y filtros de Kalman en Python. Proporciona un marco para construir filtros lineales y no lineales con el fin de estimar el estado de sistemas dinámicos combinando datos de sensores ruidosos con modelos matemáticos de procesos. La biblioteca se centra en la estimación probabilística de estados, utilizando actualización bayesiana recursiva y modelado matemático de espacio de estados para refinar las creencias sobre los estados del sistema. Incluye utilidades para simular sistemas dinámicos, lo que permite a los usuarios generar trayectorias sintéticas y observaciones de sensores para validar algoritmos de seguimiento frente a datos de referencia conocidos. La colección cubre conceptos fundamentales en ingeniería de sistemas de control, navegación robótica y fusión de datos de sensores. Está estructurada como una guía completa que combina explicaciones teóricas con implementaciones prácticas de código para calcular distribuciones de probabilidad y gestionar la incertidumbre en entornos dinámicos.

    Offers a toolkit for calculating probability distributions of system states using iterative Bayesian updates.

    Jupyter Notebook
    Ver en GitHub↗19,050
  • rem0o/fancontrol.releasesAvatar de Rem0o

    Rem0o/FanControl.Releases

    18,777Ver en GitHub↗

    FanControl is a system utility for Windows that provides comprehensive thermal management and fan speed regulation. It functions as a background service, ensuring that cooling configurations remain active from system boot without requiring an active user session. The software distinguishes itself through a modular plugin architecture that supports proprietary hardware controllers, liquid cooling systems, and third-party sensors. Users can define complex cooling behaviors by mapping multiple temperature inputs to fan outputs using graphical curves and mathematical operations, while incorporati

    Combines multiple temperature inputs from various hardware sources to drive complex cooling logic.

    controlcpucurves
    Ver en GitHub↗18,777
  • wled/wledAvatar de wled

    wled/WLED

    18,249Ver en GitHub↗

    WLED is a web-based firmware designed for ESP8266 and ESP32 microcontrollers to manage addressable LED strips and matrices. It functions as a comprehensive IoT lighting automation system, providing the tools to control individual pixels, define logical segments, and execute dynamic lighting effects. The platform supports a wide range of hardware configurations, including matrix panels and non-addressable LED arrays, while offering granular control over brightness, color palettes, and animation speed. The project distinguishes itself through its extensive support for networked orchestration an

    Reads signals from analog sensors to dynamically adjust lighting properties like brightness and speed.

    C++esp32esp8266hacktoberfest
    Ver en GitHub↗18,249
  • microsoft/airsimAvatar de microsoft

    microsoft/AirSim

    17,956Ver en GitHub↗

    AirSim is a high-fidelity simulation platform designed for the development and testing of autonomous vehicles. Built as a plugin for game engines, it provides a physics-based environment that models vehicle dynamics and sensor data, serving as a foundation for robotics research, computer vision training, and reinforcement learning. The platform distinguishes itself through its support for hardware-in-the-loop and software-in-the-loop testing, allowing developers to validate control logic and firmware against real-world signals or concurrent processes. It offers extensive programmatic control

    Serves as a hardware-in-the-loop testing tool for validating flight controller firmware against simulated dynamics.

    C++aiairsimartificial-intelligence
    Ver en GitHub↗17,956
  • marlinfirmware/marlinAvatar de MarlinFirmware

    MarlinFirmware/Marlin

    17,433Ver en GitHub↗

    Marlin is a firmware platform designed for 3D printers and CNC machines that translates manufacturing instructions into precise hardware operations. It functions as a G-code interpreter, parsing text-based commands to manage multi-axis motion, thermal regulation, and material delivery systems. By operating independently of a host computer, the system enables a standalone manufacturing workflow through the direct processing of files from local storage. The firmware distinguishes itself through a modular hardware abstraction layer that supports a wide range of microcontroller configurations. It

    Executes sensor-based calibration routines to ensure geometric accuracy and consistent material adhesion across the build surface.

    C++3d-printingarduinoatmel
    Ver en GitHub↗17,433
Ant.123456…10Siguiente
  1. Home
  2. Hardware & IoT
  3. Embedded Systems And Robotics

Explorar subetiquetas

  • Embedded System FlashersTools for writing firmware or OS images to storage media for embedded hardware. **Distinguishing note:** Specifically targets single-board computers and custom hardware platforms.
  • Embedded VisualizationGraphical tools optimized for resource-constrained hardware environments. **Distinguishing note:** Focuses on low-latency, low-dependency visualization for embedded devices.
  • Hardware-in-the-Loop Simulators4 sub-etiquetasTesting environments that integrate software modules with physical or simulated hardware control systems. **Distinguishing note:** Focuses on real-time validation of algorithms against hardware interfaces.
  • Robotics And Autonomous Systems14 sub-etiquetasFrameworks, middleware, and systems designed to control autonomous robots and unmanned aerial vehicles.
  • Sensor Processing5 sub-etiquetasAlgorithms and software that combine data from multiple sensors to produce accurate real-time environmental information.