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Marco Pavone
@drmapavone
Prof @Stanford, Distinguished Research Scientist and AV research lead @nvidia. PhD from @MITAeroAstro. Robotics, autonomous systems, AI. Opinions are my own.
加入 November 2018
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Humanoid retargeting and inverse kinematics in microseconds, running entirely on CPU! Introducing frax.ik, a high-performance library for humanoid retargeting and inverse kinematics. Orders of magnitude faster than existing alternatives, frax.ik delivers high-quality results while avoiding common motion artifacts such as foot skidding, floor penetration, and self-collisions. Designed for both real-time teleoperation and offline dataset processing, frax.ik enables responsive motion retargeting at runtime and efficient generation of high-quality motion datasets for downstream robot learning and RL pipelines. Check it out: Great work led by my PhD student @danielpmorton #HumanoidRobotics# #PhysicalAI# #Robotics# @StanfordAILab @StanfordASL
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