In this paper, we introduce Haptic-Informed ACT, an advanced robotic system for pseudo oocyte manipulation, integrating multimodal information and Action Chunking with Transformers (ACT). Traditional automation methods for oocyte transfer rely heavily on visual perception, often requiring human supervision due to biological variability and environmental disturbances. Haptic-Informed ACT enhances ACT by incorporating haptic feedback, enabling real-time grasp failure detection and adaptive correction. Additionally, we introduce a 3D-printed TPU soft gripper to facilitate delicate manipulations. Experimental results demonstrate that Haptic-Informed ACT improves the task success rate, robustness, and adaptability compared to conventional ACT, particularly in dynamic environments. These findings highlight the potential of multimodal learning in robotics for biomedical automation.
@article{arxiv.2506.18212,
title = {Haptic-Informed ACT with a Soft Gripper and Recovery-Informed Training for Pseudo Oocyte Manipulation},
author = {Pedro Miguel Uriguen Eljuri and Hironobu Shibata and Maeyama Katsuyoshi and Yuanyuan Jia and Tadahiro Taniguchi},
journal= {arXiv preprint arXiv:2506.18212},
year = {2025}
}
Comments
Accepted at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2025) Project website https://tanichu-laboratory.github.io/pedro_haptic_act_iros2025/