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Xingjian Li

2 papers indexed

arxivcs.LGeess.SYmath.OC2026-07-22

End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers

Xingjian Li, Kelvin Kan, Deepanshu Verma, Krishna Kumar, Stanley Osher, Samy Wu Fung

We consider the problem of learning high-dimensional semi-global feedback controllers under hard safety constraints enforced by control barrier functions (CBFs). Incorporating CBFs into end-to-end policy training requires embedding a quadratic-program-based safety filter as an op…

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arxivcs.RO2026-07-01

Path Planning in Physically Viable World Models

Su Ann Low, Cheng-Hsi Hsiao, Xingjian Li, Adam J. Thorpe, Ufuk Topcu, Krishna Kumar

Robots deployed in unstructured outdoor environments often plan from scene reconstructions collected before deployment because operators cannot remap large or remote sites before every mission. As a result, robots must make long-horizon planning decisions using stale maps that as…

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