ADAMSim: PyBullet-Based Simulation Environment for Research on Domestic Mobile Manipulator Robots

Autores/as

DOI:

https://doi.org/10.17979/ja-cea.2025.46.12217

Palabras clave:

Simulador de robots, Gemelo digital, PyBullet, Real-to-Sim, Sim-to-Real, Manipulador Mmovil

Resumen

Este artículo presenta ADAMSim, un entorno de simulación basado en PyBullet diseñado específicamente para el Ambidextrous Domestic Autonomous Manipulator (ADAM), desarrollado para apoyar la investigación en navegación, manipulación y aprendizaje en robótica doméstica. El simulador replica con precisión la estructura y el comportamiento del robot físico, lo que permite una transferencia robusta de algoritmos entre simulación y mundo real. ADAMSim sigue un diseño modular, que incluye navegación, cinemática de brazos y manos, percepción y comunicación mediante ROS. Esta arquitectura permite la operación sincronizada entre el robot real y su gemelo digital. Se desarrollaron diversos ejemplos, que abarcan desde tareas de visión y agarre, hasta navegación y teleoperación, incluyendo experimentos ejecutados simultáneamente en el robot simulado y el real. Su diseño de código abierto y flexible convierte a ADAMSim en una herramienta poderosa para el desarrollo seguro y reproducible de algoritmos y experimentos en robótica doméstica. La plataforma también está pensada para apoyar investigaciones en mapeo de interiores, aprendizaje de manipulación avanzada y proyectos educativos, como banco de pruebas.

Biografía del autor/a

  • Adrian Prados, Universidad Carlos III de Madrid
    My name is Adrián Prados  and I am currently studying a Ph.D. in Electrical, Electronics and Automation Engineering. Since i was a kid I have been passionate about robotics and I have always wanted to investigate into this wide world. I received my degree in Industrial Electronics and Automation Engineering at UC3M in 2021 and my M.Sc. degree in Robotics and Automation at UC3M in 2023.  My interests include path planning, mapping , navigation with mobile robots, manipulation (which was the subject of my final degree project), reinforcement learning and imitation learning (the subject of my final master project). Right now I am working in the HEROITEA project, where we are developing a robot to help elder people in diferent every day actions like could be cook.    Since 2023, I am pursuing my PhD studies. The main topic of my research focuses on the application of Imitation Learning (also known as Learning from Demonstration) techniques to manipulation tasks. The idea is to facilitate the use of robots by people with no prior knowledge, allowing them to teach the robot how they want a task to be done in different environments and constraints.   Some of the project in which I am working can be seen here well as open source code available on my GitHub profile.

Referencias

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Cartel Jornadas de Automática 2025

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Publicado

01-09-2025

Número

Núm. 46 (2025)

Sección

Robótica

Licencia

Derechos de autor 2025 Adrian Prados, Gonzalo Espinoza, Alberto Mendez, Alicia Mora, Santiago Garrido, Ramon Barber

Creative Commons License

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.