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Lucas Igel

1 accepted papers

2022

MLNav: Learning to Safely Navigate on Martian Terrains

RA-L 2022

We present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MLNav</i> , a learning-enhanced path planning framework for safety-critical and resource-limited systems operating in complex environments, such as rovers navigating on Mars. MLNav makes judi

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