휴머노이드 로봇 세계 전략 : 동서 모델 경쟁 분석(2025년)

Current progress in humanoid robotics is centered on optimizing vision-language-action (VLA) models, integrating multimodal data, and enhancing instruction comprehension as well as the ability to interpret human intent. Training relies heavily on world models, human video data, and VR-based remote training, with increasing emphasis on first-person perspectives to strengthen perception. While the ultimate goal is to achieve general-purpose humanoids, development remains constrained by significant challenges, leading Western and Chinese companies to pursue divergent technological pathways.

SAMPLE VIEW

Key Highlights:

• Humanoid robotics focuses on optimizing vision-language-action (VLA) models and enhancing multimodal data integration.
• Improving instruction comprehension and human intent interpretation is a core development area.
• Training relies heavily on world models, human video data, and VR-based remote training, with growing emphasis on first-person perspectives.
• The ultimate goal is to achieve general-purpose humanoids, but major technical challenges persist.
• Western and Chinese companies are pursuing different technological pathways in response.

Table of Contents

1. Vision Models as the Core of Robotic Perception

• Figure 1: Humanoid Robot Model Operation Framework
• Figure 2: Training Data for Humanoid Robots
• Table 1: Comparison of First-Person and Third-Person View Algorithms
• Figure 3: Apple HAT Model Overview
• Table 2: Summary of First-Person Datasets

2. Strategic Moves by Humanoid Robot Model Developers

• Figure 4: ViLLA Architecture

3. TRIIs View