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DiffCVaR: Reinforcement Learning for Risk Adaptation via Differentiable CVaR Barrier Functions
Planning through crowded environments under uncertain obstacle motions remains difficult, as stochastic interactions often induce overly conservative behavior or reduced efficiency. To address this challenge, we propose an end-to-end risk adaptation framework for crowd navigation under obstacle-moti
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