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Grasping state estimation of printable soft gripper using electro-conductive yarn
Takahiro Matsuno1, Zhongkui Wang1, Shinichi Hirai1
1Department of Robotics, Ritsumeikan University, Noji Higashi, 1-1-1, Kusatsu, Shiga 525-8577 Japan.
Robotics and Biomimetics
|November 25, 2017
Summary
A new method uses electro-conductive yarn to sense how well a 3D-printed soft gripper grasps food. This low-cost sensor accurately estimates the grasping state, advancing food automation.
Area of Science:
- Robotics and Automation
- Materials Science
- Sensor Technology
Background:
- Automated food handling is crucial for mass-producing box lunches.
- 3D-printable soft grippers offer a simple solution for food material manipulation.
- Existing grippers lack integrated sensing capabilities for grasping state estimation.
Purpose of the Study:
- To develop and validate a novel sensing method for printable soft grippers using electro-conductive yarn.
- To assess the cost-effectiveness and ease of use of electro-conductive yarn as a sensor.
- To enable accurate estimation of the grasping state in automated food handling systems.
Main Methods:
- Integration of electro-conductive yarn into a prototype 3D-printable soft gripper.
- Experimental verification of the yarn's resistance change due to stretching during grasping.
- Correlation analysis between measured resistance and the actual grasping state.
Main Results:
- Electro-conductive yarn successfully integrated into the soft gripper.
- Changes in yarn resistance directly corresponded to the gripper's grasping state.
- Experimental results demonstrated high accuracy in estimating the grasping state.
Conclusions:
- Electro-conductive yarn provides a viable, low-cost sensing solution for printable soft grippers.
- The proposed method accurately estimates the grasping state, enhancing robotic food handling.
- This technique facilitates the automation of commercial box lunch production.
