Researchers have developed a small-scale robot that uses body load sensing to dynamically adjust its gait and maintain stable locomotion across challenging granular surfaces.
A new study examines the growing trend of students leveraging AI tools for computational modeling assignments in physics courses.
The field is rapidly evolving with powerful new artificial intelligence tools, but translating research into real-world clinical impact presents significant hurdles.
New research introduces a rigorous framework and dataset to evaluate how closely humanoid robot motion mimics natural human movement.
Researchers have developed a human-robot interaction system that allows users to direct robots with a simple glance at an object combined with a spoken command.
A new evaluation of the Boltz-2 foundation model reveals efficient structural predictions, but highlights significant limitations in accurately forecasting protein-ligand binding affinities.
Researchers have developed an agentic system that can control a diverse range of robots using only natural language instructions, eliminating the need for platform-specific training.
A new analysis of decades-old data from the Large Electron-Positron collider demonstrates the potential of artificial intelligence to refine our understanding of fundamental particle interactions.
![A novel basis function design embeds material distribution via [latex]\arg\max[/latex] evaluation of a score field, enabling optimized swimmer trajectories-achieved through joint optimization-that outperform both sequential optimization and neural field encoding methods prone to lateral drift.](https://arxiv.org/html/2603.06497v1/x1.png)
Researchers have developed a new method for simultaneously optimizing a soft robot’s shape, material properties, and actuation, paving the way for more adaptable and efficient designs.
Artificial intelligence and self-driving laboratories are poised to dramatically speed up the design of catalysts and chemical reactions.