MPCC using arc-length parameterization and a compact coupled-dynamics model enables precise trajectory tracking for bird-scale ornithopters without predefined speed profiles.
Mpcc++: Model predictive contouring control for time- optimal flight with safety constraints
3 Pith papers cite this work. Polarity classification is still indexing.
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NavRL++ improves sim-to-real transfer for RL navigation via empirical analysis of perturbations, perturbation-aware fine-tuning, and a Transformer temporal policy, with real-world validation showing outperformance over learning baselines and parity with optimization planners in static cases.
TAG-K combines greedy randomized Kaczmarz row selection with tail averaging to deliver faster convergence and noise robustness for online inertial parameter estimation in robotics.
citing papers explorer
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Accurate Trajectory Tracking with MPCC for Flapping-Wing MAVs
MPCC using arc-length parameterization and a compact coupled-dynamics model enables precise trajectory tracking for bird-scale ornithopters without predefined speed profiles.
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NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation
NavRL++ improves sim-to-real transfer for RL navigation via empirical analysis of perturbations, perturbation-aware fine-tuning, and a Transformer temporal policy, with real-world validation showing outperformance over learning baselines and parity with optimization planners in static cases.
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TAG-K: Tail-Averaged Greedy Kaczmarz for Computationally Efficient and Performant Online Inertial Parameter Estimation
TAG-K combines greedy randomized Kaczmarz row selection with tail averaging to deliver faster convergence and noise robustness for online inertial parameter estimation in robotics.