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Hauptverfasser: Eljuri, Pedro Miguel Uriguen, Shibata, Hironobu, Katsuyoshi, Maeyama, Jia, Yuanyuan, Taniguchi, Tadahiro
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2506.18212
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author Eljuri, Pedro Miguel Uriguen
Shibata, Hironobu
Katsuyoshi, Maeyama
Jia, Yuanyuan
Taniguchi, Tadahiro
author_facet Eljuri, Pedro Miguel Uriguen
Shibata, Hironobu
Katsuyoshi, Maeyama
Jia, Yuanyuan
Taniguchi, Tadahiro
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2506_18212
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Haptic-Informed ACT with a Soft Gripper and Recovery-Informed Training for Pseudo Oocyte Manipulation
Eljuri, Pedro Miguel Uriguen
Shibata, Hironobu
Katsuyoshi, Maeyama
Jia, Yuanyuan
Taniguchi, Tadahiro
Robotics
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.
title Haptic-Informed ACT with a Soft Gripper and Recovery-Informed Training for Pseudo Oocyte Manipulation
topic Robotics
url https://arxiv.org/abs/2506.18212