Science

A new framework empowers robots to replicate human manipulation skills by fusing visual perception with tactile feedback and 3D understanding.

Researchers are exploring how to train artificial intelligence to identify and propose promising research directions, mirroring the intuitive ‘taste’ of experienced scientists.

Researchers have developed a 13-DOF pneumatically actuated upper-body robot and demonstrated a data-driven control strategy that overcomes inherent time delays for smoother, more accurate movements.

Documenting the complex interactions within autonomous AI agents requires a clear, standardized approach, and this paper proposes a practical solution based on established software architecture principles.

New research reveals a growing disconnect between how AI is designed for the workplace and what workers actually need to feel engaged and fulfilled.

A new Bayesian framework systematically searches for the underlying equations governing dynamic systems, even when key physical principles are unknown.

Research shows that artificial intelligence can assist designers in creating effective electronic textile sensor layouts for accurate motion capture.

A new architecture proposes fully autonomous systems capable of organizing and analyzing vast streams of news data, moving beyond assistance to independent computational journalism.

A project-based learning framework combining robotics and agile methodologies empowers students to tackle real-world challenges like automated disassembly and contribute to a circular economy.

A new multi-agent framework combines the power of artificial intelligence with climate and social science to offer a deeper understanding of complex, interacting systems.