A robot that performs well in a controlled simulation can struggle when real-world conditions don't match what it was trained to expect.

Trainee Lightning Wakute operates a robotic welding arm while Eileen DeCora watches at Nebraska Innovation Studio. (Ani Schutz/Silicon Prairie News) A new industry-certified training program supported ...

MIT researchers developed a technique to combine robotics training data across domains, modalities, and tasks using generative AI models. They create a combined strategy from several different ...

As Californian companies race to manufacture and deploy thousands of humanoid robots in the coming year, another new class of ...

Teaching robots to manipulate objects with human-like dexterity remains one of the biggest challenges ...

The Genesis Project represents a significant leap forward in the convergence of generative AI and physics simulation, reshaping the way robots are trained and developed. By integrating innovative ...

Lightweight Five-Camera System Balances the Data Requirements of Leading Research Labs With the Comfort and Usability ...

China’s robot schools are training humanoids through repetition, VR-guided demonstrations, and shared data to prepare them for real-world work.

What if robots could learn to handle objects without watching humans? The new way training data is created can shape what robots learn.

ABB Robotics is collaborating with California bionics company, PSYONIC, to advance robotic gripping and dexterity using a new ...

China is set to launch its first heterogeneous humanoid robot training facility in Shanghai this July. The facility, part of the National and Local Co-Built Humanoid Robotics Innovation Center, will ...