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rebuilding site Sun Mar 30 11:22:34 AM EDT 2025
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‎404.html‎

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‎authors/abhinavsharma/index.html‎

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‎authors/abhinavsharma/index.xml‎

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<description>Recent content on A²R Lab</description>
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‎authors/admin/index.html‎

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<p>The A²R Lab at Barnard College, Columbia University, focuses on <strong>optimizing robotic systems at all scales</strong> by developing, optimizing, implementing, and evaluating next-generation algorithms and edge computational systems, through algorithm-hardware-software co-design (e.g., <a href="/publication/mpcgpu">MPCGPU</a>, <a href="/publication/grid">GRiD</a>, <a href="/publication/tinympc">TinyMPC</a>). As such, our research is at the intersection of Robotics and Computer Architecture, Embedded Systems, Numerical Optimization, and Machine Learning.</p>
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<p>We also want to <strong>promote a responsible, sustainable, and accessible future for robotics and edge computing</strong>, 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., <a href="/publication/scalingtinyml4d">Global TinyML Education</a>, <a href="/publication/paroptrobcourse">Parallel Optimization for Robotics</a>).</p>
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<p>The A²R Lab at Barnard College, Columbia University, focuses on <strong>optimizing robotic systems at all scales</strong> by developing, optimizing, implementing, and evaluating next-generation algorithms and edge computational systems, through algorithm-hardware-software co-design (e.g., <a href="/publication/mpcgpu/">MPCGPU</a>, <a href="/publication/grid/">GRiD</a>, <a href="/publication/tinympc/">TinyMPC</a>). As such, our research is at the intersection of Robotics and Computer Architecture, Embedded Systems, Numerical Optimization, and Machine Learning.</p>
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<p>We also want to <strong>promote a responsible, sustainable, and accessible future for robotics and edge computing</strong>, 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., <a href="/publication/scalingtinyml4d/">Global TinyML Education</a>, <a href="/publication/paroptrobcourse/">Parallel Optimization for Robotics</a>).</p>
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‎authors/admin/index.xml‎

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<description>The A²R Lab at Barnard College, Columbia University, 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.&#xA;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.</description>
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‎authors/aleksandrafaust/index.xml‎

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<title>Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots</title>
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<description>Tiny robot learning lies at the intersection of embedded systems, robotics, and ML, compounding the challenges of these domains. This paper gives a brief survey of the tiny robot learning space, elaborates on key challenges, and proposes promising opportunities for future work in ML system design.</description>
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<title>The Role of Compute in Autonomous Aerial Vehicles</title>
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<description>By combining MAVBench (our tool-set, which consists of (1) a closed-loop real-time feedback simulator and (2) an end-to-end benchmark suite comprised of state-of-the-art kernels), analytical modeling, and an understanding of various compute impacts, we show up to 2X and 1.8X improvements for mission time and mission energy for two optimization case studies. Our investigations, as well as our optimizations, show that cyber-physical co-design, a methodology with which both the cyber and physical processes/quantities of the robot are developed with consideration of one another, similar to hardware-software co-design, is necessary for arriving at the design of the optimal robot.</description>
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‎authors/alessandrogrande/index.html‎

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