German Research Center for Artificial Intelligence | Torque-limited simple pendulum: A toolkit for getting started with underactuated robotics @dfkivideo | Uploaded 2 years ago | Updated 3 hours ago
There are many, wildly different approaches to robotic control. Underactuated robots are systems for which it is not possible to dictate arbitrary accelerations to all joints. Hence, a controller cannot be used to override the system dynamics and force the system on a desired trajectory as it often is done in classical control techniques. A torque-limited pendulum is arguably the simplest underactuated robotic system and thus is a suitable system to study, test and benchmark different controllers.
This project describes the hardware (Computer-aided design (CAD) models, Bill Of Materials (BOM), etc.) required to build a physical pendulum system and provides the software (Unified Robot Description Format (URDF) models, simulation and controller) to control it. It provides a setup for studying established and novel control methods on a simple torque-limited pendulum, and targets students and beginners of robotic control. In this video we will cover mechanical and electrical setup of the test bed, introduce offline trajectory optimization methods and showcase model-based as well as data-driven controllers. The entire hardware and software description is open-source available under github.com/dfki-ric-underactuated-lab/torque_limited_simple_pendulum
Authors
Project Supervisor: Shivesh Kumar
Software Maintainer: Felix Wiebe
Hardware Maintainer: Jonathan Babel
Contributors: Daniel Harnack, Heiner Peters, Shubham Vyas, Melya Boukheddimi, Mihaela Popescu
Funding
This work has been performed in the VeryHuman project funded by the German Aerospace Center (DLR) with federal funds (Grant Number: FKZ 01IW20004) from the Federal Ministry of Education and Research (BMBF) and is additionally supported with project funds from the federal state of Bremen for setting up the Underactuated Robotics Lab (Grant Number: 201-001-10-3/2021-3-2).
#robotics #underactuated #pendulum #optimalcontrol #modelbased #energyshaping #lqr #datadriven #reinforcementlearning #SAC #trajectoryoptimization #directcollocation #FDDP #DFKI #roboticsinnovationcenter
Software Credits
Drake, Russ Tedrake and the Drake Development Team, "Drake: Model-based design and verification for robotics", 2019,
https://drake.mit.edu
Crocoddyl, Carlos Mastalli, Rohan Budhiraja and Nicolas Mansard and others, "Crocoddyl: a fast and flexible optimal control library for robot control under contact sequence, 2019, github.com/loco-3d/crocoddyl/wikis/home
TensorFlow, TensorFlow was developed by the Google Brain team for internal Google use. It was released under the Apache License 2.0 in 2015,
tensorflow.org
There are many, wildly different approaches to robotic control. Underactuated robots are systems for which it is not possible to dictate arbitrary accelerations to all joints. Hence, a controller cannot be used to override the system dynamics and force the system on a desired trajectory as it often is done in classical control techniques. A torque-limited pendulum is arguably the simplest underactuated robotic system and thus is a suitable system to study, test and benchmark different controllers.
This project describes the hardware (Computer-aided design (CAD) models, Bill Of Materials (BOM), etc.) required to build a physical pendulum system and provides the software (Unified Robot Description Format (URDF) models, simulation and controller) to control it. It provides a setup for studying established and novel control methods on a simple torque-limited pendulum, and targets students and beginners of robotic control. In this video we will cover mechanical and electrical setup of the test bed, introduce offline trajectory optimization methods and showcase model-based as well as data-driven controllers. The entire hardware and software description is open-source available under github.com/dfki-ric-underactuated-lab/torque_limited_simple_pendulum
Authors
Project Supervisor: Shivesh Kumar
Software Maintainer: Felix Wiebe
Hardware Maintainer: Jonathan Babel
Contributors: Daniel Harnack, Heiner Peters, Shubham Vyas, Melya Boukheddimi, Mihaela Popescu
Funding
This work has been performed in the VeryHuman project funded by the German Aerospace Center (DLR) with federal funds (Grant Number: FKZ 01IW20004) from the Federal Ministry of Education and Research (BMBF) and is additionally supported with project funds from the federal state of Bremen for setting up the Underactuated Robotics Lab (Grant Number: 201-001-10-3/2021-3-2).
#robotics #underactuated #pendulum #optimalcontrol #modelbased #energyshaping #lqr #datadriven #reinforcementlearning #SAC #trajectoryoptimization #directcollocation #FDDP #DFKI #roboticsinnovationcenter
Software Credits
Drake, Russ Tedrake and the Drake Development Team, "Drake: Model-based design and verification for robotics", 2019,
https://drake.mit.edu
Crocoddyl, Carlos Mastalli, Rohan Budhiraja and Nicolas Mansard and others, "Crocoddyl: a fast and flexible optimal control library for robot control under contact sequence, 2019, github.com/loco-3d/crocoddyl/wikis/home
TensorFlow, TensorFlow was developed by the Google Brain team for internal Google use. It was released under the Apache License 2.0 in 2015,
tensorflow.org
