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GaussFly: Contrastive Reinforcement Learning for Visuomotor Policies in 3D Gaussian Fields

Description

Learning visuomotor policies for Autonomous Aerial Vehicles (AAVs) relying solely on monocular vision is an attractive yet highly challenging paradigm. Existing end-to-end learning approaches directly map high-dimensional RGB observations to action commands, which frequently suffer from low sample efficiency and severe sim-to-real gaps due to the visual discrepancy between simulation and physical domains. To address these long-standing challenges, we propose GaussFly, a novel framework that expl

Source

http://arxiv.org/abs/2604.05062v1