What This Research Area Covers
AI robotics research studies how learned models can control physical robots — navigation, manipulation, and decision-making in the real world — increasingly incorporating techniques from language and vision models into embodied systems.
Why It Matters
Bridging the gap between digital AI capability and physical-world action remains a significant challenge, and robotics research is where many core AI techniques get tested against the unpredictability of the real world.
Current Research Directions
Applying large language and vision model techniques to robotic control, improving sample efficiency (learning from fewer real-world trials), and simulation-to-real-world transfer are all active areas.
Related Pages
Frequently Asked
How does this relate to language models?
Increasingly, robotics research incorporates language and vision model techniques, letting robots follow natural-language instructions or reason about visual scenes.
What's 'sim-to-real transfer'?
Training a robot's control policy in simulation (cheaper and faster) and then transferring that learning to a real physical robot, a significant and active research challenge.
Which companies are active in AI robotics research?
Several major labs have published robotics-adjacent research; check individual company pages for specific contributions.
Where can I learn about a specific robotics-focused model?
Check our Companies directory and News for company-specific robotics announcements.