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20092025
most citedAn Efficient Production Process for Extracting Salivary Glands from Mosquitoes

6 citations · 15 across the 29 of their papers we have counts for

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21 papers · 1 filter

cs.RO2024

RaggeDi: Diffusion-based State Estimation of Disordered Rags, Sheets, Towels and Blankets

Jikai Ye, Wanze Li, Shiraz Khan +1

Cloth state estimation is an important problem in robotics. It is essential for the robot to know the accurate state to manipulate cloth and execute tasks such as robotic dressing,…

cs.RO2024

Grasping by Hanging: a Learning-Free Grasping Detection Method for Previously Unseen Objects

Wanze Li, Wan Su, Gregory S. Chirikjian

This paper proposes a novel learning-free three-stage method that predicts grasping poses, enabling robots to pick up and transfer previously unseen objects. Our method first ident…

cs.RO2024

Design, Calibration, and Control of Compliant Force-sensing Gripping Pads for Humanoid Robots

Yuanfeng Han, Boren Jiang, Gregory S. Chirikjian

This paper introduces a pair of low-cost, light-weight and compliant force-sensing gripping pads used for manipulating box-like objects with smaller-sized humanoid robots. These pa…

cs.RO2024

RAIL: Robot Affordance Imagination with Large Language Models

Ceng Zhang, Xin Meng, Dongchen Qi +1

This paper introduces an automatic affordance reasoning paradigm tailored to minimal semantic inputs, addressing the critical challenges of classifying and manipulating unseen clas…

cs.RO2023

Prepare the Chair for the Bear! Robot Imagination of Sitting Affordance to Reorient Previously Unseen Chairs

Xin Meng, Hongtao Wu, Sipu Ruan +1

In this letter, a paradigm for the classification and manipulation of previously unseen objects is established and demonstrated through a real example of chairs. We present a novel…

cs.RO2023

PRIMP: PRobabilistically-Informed Motion Primitives for Efficient Affordance Learning from Demonstration

Sipu Ruan, Weixiao Liu, Xiaoli Wang +2

This paper proposes a learning-from-demonstration method using probability densities on the workspaces of robot manipulators. The method, named "PRobabilistically-Informed Motion P…