3 papers
cs.RO2026
Predicting Grasping Compliance in Robotic Hands through Analytical-Model-Informed Neural Networks
Qianwen Zhao, Long Wang
In robotic manipulation studies, grasping is often treated as a binary success or failure problem, usually defined by whether the object simply stays in the hand. For forceful tool…
cs.RO2025
Is Image-based Object Pose Estimation Ready to Support Grasping?
Eric C. Joyce, Qianwen Zhao, Nathaniel Burgdorfer +2
We present a framework for evaluating 6-DoF instance-level object pose estimators, focusing on those that require a single RGB (not RGB-D) image as input. Besides gaining intuition…
cs.RO2025
Consensus-Driven Uncertainty for Robotic Grasping based on RGB Perception
Eric C. Joyce, Qianwen Zhao, Nathaniel Burgdorfer +2
Deep object pose estimators are notoriously overconfident. A grasping agent that both estimates the 6-DoF pose of a target object and predicts the uncertainty of its own estimate c…