PBRS-augmented RL trained in simple settings transfers zero-shot to complex UAV environments when wrapped with a CLF-CBF-QP safety filter, yielding shorter missions and formal safety guarantees.
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A hybrid offline-online approach adapts neural robot dynamics models via low-rank second-order updates to enable robust predictive tracking control on quadrotors in novel conditions.
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Zero-Shot, Safe and Time-Efficient UAV Navigation via Potential-Based Reward Shaping, Control Lyapunov and Barrier Functions
PBRS-augmented RL trained in simple settings transfers zero-shot to complex UAV environments when wrapped with a CLF-CBF-QP safety filter, yielding shorter missions and formal safety guarantees.
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Adapting Neural Robot Dynamics on the Fly for Predictive Control
A hybrid offline-online approach adapts neural robot dynamics models via low-rank second-order updates to enable robust predictive tracking control on quadrotors in novel conditions.