A key component of many robotics model-based planning and control algorithms is physics predictions, that is, forecasting a sequence of states given an initial state and a sequence of controls. This process is slow and a major computational bottleneck for robotics planning algorithms. Parallel-in-time integration methods can help to leverage parallel computing to accelerate physics predictions and thus planning. The Parareal algorithm iterates between a coarse serial integrator and a fine parallel integrator. A key challenge is to devise a coarse model that is computationally cheap but accurate enough for Parareal to converge quickly. Here, we investigate the use of a deep neural network physics model as a coarse model for Parareal in the context of robotic manipulation. In simulated experiments using the physics engine Mujoco as fine propagator we show that the learned coarse model leads to faster Parareal convergence than a coarse physics-based model. We further show that the learned coarse model allows to apply Parareal to scenarios with multiple objects, where the physics-based coarse model is not applicable. Finally, we conduct experiments on a real robot and show that Parareal predictions are close to real-world physics predictions for robotic pushing of multiple objects. Videos are at https://youtu.be/wCh2o1rf-gA.


    Access

    Download


    Export, share and cite



    Title :

    Parareal with a learned coarse model for robotic manipulation


    Contributors:

    Publication date :

    2020-09-23


    Remarks:

    2-s2.0-85091274340



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    510 / 629




    Modular robotic manipulation

    BRUEMMER DAVID J | European Patent Office | 2019

    Free access

    Learning robotic cloth manipulation

    Verleysen, Andreas | BASE | 2022

    Free access


    ROBOTIC MANIPULATION OF PV MODULES

    SCHNEIDER TRAVIS / ALLEN III ARTHUR REEG / SGROI AMANDA | European Patent Office | 2021

    Free access

    Robotic manipulation of PV modules

    ALLEN ARTHUR REEG / SGROI AMANDA / SCHNEIDER TRAVIS | European Patent Office | 2023

    Free access