DAVIS: A Depth-Only End-to-End Active-Vision Framework for Humanoid Soccer Skills

arXiv:2609.28175 · cs.RO · Submitted 2026-09-23 · Read on arXiv

cs.RO

Submitted: 2026-09-23

Updated: 2026-09-23

Project page: https://thusi-lab.github.io/DAVIS

Terminology

• Actor — 45× in this paper · explained in 3 episodes
• Ablation — 21× in this paper · explained in 1 episode
• Active Vision — 14× in this paper · explained in 1 episode
• Reinforcement Learning — 10× in this paper · explained in 4 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Regularization — 7× in this paper · explained in 3 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 4× in this paper · explained in 2 episodes
• Angular Error — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Active Perception — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• International Conference on Robotics and Automation — 1× in this paper
• Reward Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes

Sources

• HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots

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