NVIDIA Research is driving a transition in robotics from scripted automation toward embodied autonomy, where machines can navigate and interact with unpredictable real-world environments.
By utilizing simulation-to-real transfer, developers can train robots in digital environments to master complex tasks—such as parallel arm coordination, precise assembly, and grasping tangled objects—without relying on manual real-world data.
The core innovation lies in creating generalizable frameworks that allow diverse robot bodies to adapt their movements and reasoning skills to new settings with high reliability.
Ultimately, this research aims to bridge the gap between virtual training and physical deployment, ensuring robots can perceive and act with human-like dexterity and intelligence.
Through a series of research papers presented at ICRA 2026, the company highlighted breakthroughs in robotic navigation, planning speed, and manual dexterity.
NVIDIA Blog
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