College - Author 1
College of Engineering
Department - Author 1
Computer Engineering Department
Advisor
Siavash Farzan, College of Engineering, Electrical Engineering Department
Funding Source
The Noyce School of Applied Computing and the Electrical Engineering Department
Date
10-2024
Abstract/Summary
This research investigates how to achieve an optimal grasp of an apple using a four-finger soft robotic grasper equipped with force-resistive sensors. Specifically, we sought to determine whether a convolutional neural network (CNN) could accurately classify the grasper's state and recommend adjustments ("in," "out," or "good" grasp) based on tactile data from the sensors. Spatiotemporal tactile images were developed from the sensors and fed into our CNN, achieving near 100% accuracy on unseen test data. This work suggests that CNN-based processing of tactile images can be a powerful tool for real-time control of soft robotic grippers.
October 1, 2024.
Included in
URL: https://digitalcommons.calpoly.edu/ceng_surp/76