The A²R Lab at Barnard College, Columbia University, focuses 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 (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 improve the accessibility of STEM education. We therefore 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 (e.g., Global TinyML Education, Parallel Optimization for Robotics).
[9/6/24] We were awarded an NSF CSSI Grant to build an Accessible GPU-Accelerated Edge Optimal Control Library and Benchmarks!
[7/16/24] Our MPCGPU paper won the Best Poster Award at the IEEE-RAS TC on Model-Based Optimization for Robotics Virtual Poster Session!
[6/7/24] We and our international collaborators were awarded an IEEE-RAS Technical Education Program Grant to run an “Optimization for Robotics Summer School” to be held in Summer 2025!
[5/16/24] Our TinyMPC paper won the Best Paper in Automation and was a finalist for Best Conference Paper and Best Student Paper at the 2024 IEEE International Conference on Robotics and Automation (ICRA)!