AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work presents WOLF, a world-model-guided framework that predicts future observations to enhance autonomous exploration and reduces mean terminal time in simulations and onboard deployment of the learned model for online inference during physical flight.
Extensive experiments across challenging manipulation settings, including LIBERO, LIBERO-Plus, the RoboTwin perturbation suite, and real-world tasks, demonstrate that MixVLA improves overall zero-shot robustness while retaining strong in-domain performance.
Robust navigation in cluttered environments remains a fundamental challenge for quadrotors, particularly when strong wind disturbances arise, which perturb vehicle dynamics, limit control authority, and substantially increase collision risk. Existing learning-based navigation policies typically rely on obstacle percept...
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