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Submitted to RA-L: Lightweight Actuation-Space Learning for Soft Robotic Grasping

less than 1 minute read

Published:

Whole-body soft robotic grasping with SpiRob

We recently submitted our paper “Lightweight Learning from Actuation-Space Demonstrations via Flow Matching for Whole-Body Soft Robotic Grasping” to IEEE Robotics and Automation Letters (RA-L). In this work, we show that a Rectified Flow–based policy learned directly in actuation space can achieve 97.5% grasp success with only 30 demonstrations, while generalizing across the workspace and to object size and speed variations by leveraging the embodied mechanical intelligence of a soft spiral robot (SpiRob).

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publications

Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.