The A²R Lab at Barnard College, Columbia University, focusses on developing and implementing open-source algorithms for dynamic motion planning and control of robots by exploiting both the mathematical structure of algorithms and the design of computational platforms. As such, our research is at the intersection of Robotics and Computer Architecture, Embedded Systems, Numerical Optimization, and Machine Learning. You can find our research code both in this Organization github.com/A2R-Lab and in the Hardware Acceleration for Robotics Organization github.com/robot-acceleration.
We also want to improve the accessibility of STEM education. We undertake research to understand and improve diversity, equity, inclusion, and belonging in STEM education globally and explore ways to design new interdisciplinary, project-based, open-access courses that lower the barrier to entry of cutting edge topics like robotics, parallel programming, and embedded machine learning. As a part of this effort we help lead the Tiny Machine Learning Open Education Initiative (TinyMLedu): TinyMLedu.org.
To learn more about our lab please visit our website: https://a2r-lab.org/.
