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@A2R-Lab

The Accessible and Accelerated Robotics Lab (A²R Lab)

The Accessible and Accelerated Robotics Lab (A²R Lab)

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The A²R Lab focuses on optimizing robotic systems at all scales by developing, optimizing, implementing, and evaluating next-generation algorithms and edge computational systems, through algorithm-hardware-software co-design (e.g., MPCGPU, GRiD, TinyMPC). As such, our research is at the intersection of Robotics and Computer Architecture, Embedded Systems, Numerical Optimization, and Machine Learning.

We also want to promote a responsible, sustainable, and accessible future for robotics and edge computing, including the development of new interdisciplinary, project-based, open-access courses that lower the barriers to entry for cutting-edge topics like robotics, parallel programming, and embedded machine learning (e.g., Global TinyML Education, Parallel Optimization for Robotics).

To learn more about our lab please visit our website: https://a2r-lab.org/.

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  1. GRiD GRiD Public

    Forked from robot-acceleration/GRiD

    A GPU accelerated library for computing rigid body dynamics with analytical gradients

    Cuda 14 6

  2. GATO GATO Public

    GPU-Accelerated Trajectory Optimization

    Cuda 37 3

  3. TinySDP TinySDP Public

    Real-time semidefinite optimization for embedded robotics, RSS 2026

    C++ 8

  4. MPCGPU MPCGPU Public

    Numerical experiments for the paper: "MPCGPU: Real-Time Nonlinear Model Predictive Control through Preconditioned Conjugate Gradient on the GPU"

    Cuda 72 9

  5. HJCD-IK HJCD-IK Public

    Cuda 15 2

  6. ADMMSlack ADMMSlack Public

    Python 3 1

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