Sashimi-Bot: Autonomous Tri-manual Advanced Manipulation and Cutting of Deformable Objects

TL;DR

Sashimi-Bot is an autonomous multi-robot system that combines deep learning and sensory feedback to manipulate and cut deformable salmon loins, demonstrating advanced robotic handling of complex, variable objects.

Contribution

This work introduces Sashimi-Bot, the first autonomous multi-robot system capable of advanced manipulation and cutting of deformable, volumetric objects like salmon loins, integrating deep reinforcement learning with sensory feedback.

Findings

Successfully manipulated and cut salmon loins with variability in shape and size.

Demonstrated robustness to deformability and slipperiness of objects.

Achieved precise slicing using cooperative multi-robot control.

Abstract

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.