Design Of A Soft Gripper For Pick And Place Application

• Main Author: Low, Mun Seng
• Format: Final Year Project / Dissertation / Thesis
• Published: 2021
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utar.edu.my/4058/1/3E_1704314_FYP_report_%2D_MUN_SENG_LOW.pdf; http://eprints.utar.edu.my/4058/

Soft Robotic Gripper (SRG) emerges as a new member of the robotic family whereby it offers promising features, such as being lightweight, low cost, soft, highly compliant, easy to fabricate, and simple to control. Due to these amazing features, SRG has become one of the most promising technologies for pick and place applications in several industries, ranging from biomedical to the food industry. However, research about current SRG only focused on one of the many parameters that would affect the overall performance. A thorough theoretical understanding of how the structural parameters affect the overall performance is still missing. Besides, there is no suitable sensor available in the market as the conventional rigid sensor is not suitable for this highly compliant gripper. Therefore, the purpose of this study is to consider all contributing parameters that would affect the performance of the SRG, such as shape, length, thickness, gap shape, gap distance, and volume of the air chamber. In addition, a soft sensor based on Triboelectric Nanogenerator (TENG) mechanisms will be introduced. The parametric studies were conducted using Abaqus CAE simulation software and SolidWorks. Ecoflex 00-50 was used to fabricate the soft pneumatic actuator (SPA) and the sponge-like TENG sensor based on single electrode mode. A linear actuator attached with a syringe was used to provide pneumatic pressure to the SRG to perform pick and place applications. An improved SPA design with an extruded semi-cylinder between the SPA gap and additional 2.5 mm semi-cylindrical air chamber was proposed based on the results obtained from the parametric studies with 0.9258% performance higher than the conventional design. Next, the fabricated sponge-like TENG sensor has provided a unique peak voltage for each material and item. The obtained results allowed this project to be further extended to performing an object-recognition system enhanced with machine learning features. Lastly, the results suggested the improved SPA with a unique character is able to perform pick and place applications, and the fabricated sponge-like TENG sensor is feasible to be implemented to the SRG.