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cs.RO2026
UWB Meets Crazyflow: Simulating Degraded Feedback at Scale for Aerial Robotics
Martin Schuck, Marcel P. Rath, Yufei Hua +3
In this work, we introduce Crazyflow, an accurate, differentiable simulator built on JAX. By leveraging jit compilation via XLA, Crazyflow unifies physics and control into a single…
cs.RO2026
Learning Loco-Manipulation From SMPC Demonstrations With Sparse Offline-to-Online RL
Martin Schuck, Maks Sorokin, Simone Manni +5
Integrating locomotion and manipulation is essential for robot autonomy, but scaling standard Reinforcement Learning (RL) to complex tasks is severely bottlenecked by the slow, man…
cs.RO2026
Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX
Martin Schuck, Marcel P. Rath, Yufei Hua +3
High-quality, large-scale synthetic data from simulations is becoming a cornerstone for pushing robots' capabilities. While aerial robotics simulators have evolved to support speci…