Researchers have developed a decentralized framework and benchmark to enable robots to more effectively collaborate and navigate complex environments using natural language and shared understanding.
New research shows that training AI on interactions between experts and novices significantly improves its ability to master complex tasks and adapt to new situations.
New research details a decentralized framework enabling teams of robots to dynamically assign themselves tasks even with limited communication and uncertain outcomes.
A new system is tackling the complex challenge of automating long-term machine learning experimentation and improvement.
Researchers have developed a modeling and optimization framework to create more effective and robust locomotion for worm-inspired robots navigating challenging environments.
A new review explores how artificial intelligence is being used to model and simulate the complex interactions between human drivers and increasingly autonomous vehicles.
A new hierarchical learning framework allows humanoid robots to acquire and retain multiple skills without forgetting previous ones.
A new framework empowers researchers to automate complex workflows and unlock insights from clinical data without extensive coding or compromising privacy.
New research demonstrates a framework allowing legged robots to anticipate a partner’s actions during collaborative transport, paving the way for more natural and robust human-robot teamwork.
A new self-driving laboratory platform powered by artificial intelligence is accelerating the synthesis and characterization of complex materials.