Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX
High-quality, large-scale synthetic data from simulations is becoming a cornerstone for pushing the capabilities of robot algorithms. While aerial robotics simulators have evolved to support specialized needs such as fidelity, differentiability, and swarms independently, a unified platform that can synthesize data across all these domains is missing. In this work, we propose Crazyflow, a simulator designed to push the limits of aerial-robotics algorithm development, from model-based to data-driven methods, gradient-based to sampling-based approaches, and single-agent to multi-agent systems. Compared to existing state-of-the-art drone simulators, it achieves speeds more than an order of ma...
| Authors | Martin Schuck, Marcel P. Rath, Yufei Hua et al. |
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| Primary category | cs.RO |
| Published | 31 May 2026 |
| Last updated at source | 5 June 2026 |
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