Soft resistive network sensor and universal robotic gripper in research
Soft robotics has a lot of important roles in various fields such as the medical, electronic industry and food industry. With soft robotics, infinite degree of freedom mechanism or robot arms can be realized and built. There are a lot of soft grippers which have been built in many forms such as t...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/168019 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Soft robotics has a lot of important roles in various fields such as the medical, electronic
industry and food industry. With soft robotics, infinite degree of freedom mechanism
or robot arms can be realized and built. There are a lot of soft grippers which have been
built in many forms such as the octopus’ legs and more unimaginable forms with the
aid of hard frame as support. Hence, to build up an entire soft robot arm, soft robotic
sensors are essential to sense the changing of any input from the surroundings and give
desire output to the users. A resistive sensor that is made up of soft materials entirely is
the first step to step into the soft robotic arm and differentiate itself from the normal
sensors that are made of hard materials such as resistors, capacitors, and inductors.
In this project, the resistive network sensor was invented and used to detect changes of
the environment. The sensor is built up by silicon and carbon grease. Carbon grease has a
high resistor value and is sensitive towards external force applied to it when covered up
by silicon layers. The resistive network sensor is sensitive to stretch and elongation
happening on itself.
A soft resistive network sensor function is to identify the shape of the object by touching
the surface of the object. By Kirchhoff’s law Matrix, the soft resistive network sensor can
have unlimited N-matrix networks but due to the limitation of the testing equipment, a
maximum of 4x4 matrix network sensors can only be identified. Therefore, the author will
present 1-Directional(1-D), 2x2 network sensors and soft resistive network robot gripper.
All the matrix network mentioned are 2-Directional(2-D) sensors. |
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