Authors:
Saltanat Seitzhan
1
;
Dionisio Cartagena González
2
;
Alexis Babut
3
;
Daniel Sánchez-Martínez
2
;
Juan Antonio Micó
2
;
Chedli Bouzgarrou
3
and
Juan Antonio Corrales Ramón
1
Affiliations:
1
Universidade de Santiago de Compostela, Santiago de Compostela, Spain
;
2
AIJU Technological Institute for Children’s Products and Leisure, Alicante, Spain
;
3
Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Institut Pascal F-63000 Clermont-Ferrand, France
Keyword(s):
Sensorized Tools, Soft Robotics, Demoulding, Meat Cutting, Force Sensing, Learning by Demonstration, Collaborative Robots, Automation.
Abstract:
While robotic arms are extensively deployed in mass production environments, their application in tasks involving
deformable object manipulation remains limited due to the complex dynamics of soft materials. Addressing
this challenge requires task-specific end-effector tools capable of replicating manual operations with
precision and adaptability. Standard human tools are often incompatible with robotic systems, especially in
domains such as meat processing and doll manufacturing. This study presents the design and experimental
validation of sensor-integrated end-effectors tailored for deformable object handling: a knife tool for roboticassisted
meat cutting and a plier tool for analyzing the demoulding process in doll production. Both tools
incorporate multimodal sensing, including force/torque sensors and inertial measurement units, and are synchronized
via ROS to capture manipulation data under realistic conditions. While full cobotic manipulation
and Learning from Demonstration (
LfD) are reserved for future work, the results demonstrate the feasibility
of embedding sensing into manual and robotic tools to support future automation in soft material handling.
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