Mastering Tools Without Training: A New Approach to Robotic Dexterity
Researchers have developed a novel framework that enables robots to manipulate unfamiliar tools and complete tasks without task-specific training data.
Science
Beyond Prediction: Reframing Time Series with Dynamical Systems
A new perspective on time series analysis argues that understanding the underlying system dynamics, rather than simply forecasting future values, is crucial for robust and generalizable models.
Ask and Verify: Smarter SQL Queries with Agentic Data Exploration
A new framework, APEX-SQL, improves the accuracy of converting natural language questions into database queries by actively learning and validating its assumptions about the underlying data.
From Steel to Softness: Bridging the Grasp Gap for Robots
![The Conditional Flow Matching (CFM) framework synthesizes grasps by learning a continuous transformation-guided by a conditional velocity field [latex]\mathbf{v}_{\theta}[/latex]-from initial rigid poses generated by Anygrasp [latex]\mathcal{G}_{\text{Anygrasp}}[/latex] to target soft gripper poses [latex]\mathcal{G}_{\text{CFM}}[/latex], a process parameterized by a feed-forward MLP and conditioned on scene geometry encoded by a U-Net autoencoder into a latent vector.](https://arxiv.org/html/2602.17110v1/x2.png)
New research demonstrates a method for transferring grasp planning from traditional rigid robot grippers to the more versatile, but challenging, domain of soft robotics.
Robots Learn by Watching: Building Task Models from Limited Examples
A new approach enables robots to infer complex tasks by observing just a few demonstrations, focusing on how objects relate and change during execution.
Symmetry’s Guiding Hand: AI Predicts Stable Materials with Unprecedented Accuracy
A new generative AI framework harnesses the power of crystal symmetry to dramatically improve the prediction of stable and novel materials.
Seeing is Sensing: A 3D-Printed Optical Sensor for Soft Robotics
Researchers have developed a new soft optical sensor with an integrated lens, enabling improved light control and precision in mechanosensing applications.
Trusting the Machine: Balancing Oversight and Autonomy
As increasingly complex AI agents take on critical tasks, ensuring effective human oversight becomes paramount, but constant monitoring isn’t scalable.
Hand Signals for Helpers: A New Dataset for Robot Control in Emergencies
Researchers have created a comprehensive dataset of hand gestures designed to enable intuitive control of robots assisting first responders in critical situations.
Beyond the Initial Diagnosis: An AI Agent That Asks the Right Questions
New research details an AI system designed to improve medical diagnoses by actively seeking clarifying information from patients, rather than relying solely on initial reports.