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Main Authors: Herland, Sverre, Parag, Amit, Øye, Elling Ruud, Zhang, Fangyi, Makiyeh, Fouad, Lillienskiold, Aleksander, Singh, Abhaya Pal, Adelson, Edward H., Chaumette, Francois, Krupa, Alexandre, Corke, Peter, Misimi, Ekrem
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.11223
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author Herland, Sverre
Parag, Amit
Øye, Elling Ruud
Zhang, Fangyi
Makiyeh, Fouad
Lillienskiold, Aleksander
Singh, Abhaya Pal
Adelson, Edward H.
Chaumette, Francois
Krupa, Alexandre
Corke, Peter
Misimi, Ekrem
author_facet Herland, Sverre
Parag, Amit
Øye, Elling Ruud
Zhang, Fangyi
Makiyeh, Fouad
Lillienskiold, Aleksander
Singh, Abhaya Pal
Adelson, Edward H.
Chaumette, Francois
Krupa, Alexandre
Corke, Peter
Misimi, Ekrem
contents Advanced robotic manipulation of deformable, volumetric objects remains one of the greatest challenges due to their pliancy, frailness, variability, and uncertainties during interaction. Motivated by these challenges, this article introduces Sashimi-Bot, an autonomous multi-robotic system for advanced manipulation and cutting, specifically the preparation of sashimi. The objects that we manipulate, salmon loins, are natural in origin and vary in size and shape, they are limp and deformable with poorly characterized elastoplastic parameters, while also being slippery and hard to hold. The three robots straighten the loin; grasp and hold the knife; cut with the knife in a slicing motion while cooperatively stabilizing the loin during cutting; and pick up the thin slices from the cutting board or knife blade. Our system combines deep reinforcement learning with in-hand tool shape manipulation, in-hand tool cutting, and feedback of visual and tactile information to achieve robustness to the variabilities inherent in this task. This work represents a milestone in robotic manipulation of deformable, volumetric objects that may inspire and enable a wide range of other real-world applications.
format Preprint
id arxiv_https___arxiv_org_abs_2511_11223
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Sashimi-Bot: Autonomous Tri-manual Advanced Manipulation and Cutting of Deformable Objects
Herland, Sverre
Parag, Amit
Øye, Elling Ruud
Zhang, Fangyi
Makiyeh, Fouad
Lillienskiold, Aleksander
Singh, Abhaya Pal
Adelson, Edward H.
Chaumette, Francois
Krupa, Alexandre
Corke, Peter
Misimi, Ekrem
Robotics
Advanced robotic manipulation of deformable, volumetric objects remains one of the greatest challenges due to their pliancy, frailness, variability, and uncertainties during interaction. Motivated by these challenges, this article introduces Sashimi-Bot, an autonomous multi-robotic system for advanced manipulation and cutting, specifically the preparation of sashimi. The objects that we manipulate, salmon loins, are natural in origin and vary in size and shape, they are limp and deformable with poorly characterized elastoplastic parameters, while also being slippery and hard to hold. The three robots straighten the loin; grasp and hold the knife; cut with the knife in a slicing motion while cooperatively stabilizing the loin during cutting; and pick up the thin slices from the cutting board or knife blade. Our system combines deep reinforcement learning with in-hand tool shape manipulation, in-hand tool cutting, and feedback of visual and tactile information to achieve robustness to the variabilities inherent in this task. This work represents a milestone in robotic manipulation of deformable, volumetric objects that may inspire and enable a wide range of other real-world applications.
title Sashimi-Bot: Autonomous Tri-manual Advanced Manipulation and Cutting of Deformable Objects
topic Robotics
url https://arxiv.org/abs/2511.11223