IEEE

Communication-Efficient Module-Wise Federated Learning for Grasp Pose Detection in Cluttered Environments

Abstract: Grasp pose detection (GPD) is a fundamental capability for robotic autonomy, but its reliance on large, diverse datasets creates significant data privacy and centralization challenges.
GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
Frontiers

Multi-State Robot Posture Detection Method Based on Joint Optimization of Target-Key Point Detection

The final, formatted version of the article will be published soon. Abstract: Industrial robots are core equipment in intelligent manufacturing, and their posture detection accuracy directly ...
IEEE

Cross-Domain Grasp Pose Detection: GAN-Based Transfer Learning with the Industrial Parts Dataset

Abstract: Robotic grasping is fundamental to many practical applications yet remains a challenging computer-vision problem. However, grasp pose detection in cluttered, unstructured settings is ...