Skip to search boxSkip to navigationSkip to main content

Pose Measurement and Contact Training of a Fabric-Reinforced Inflatable Soft Robot

  • The University of Tulsa
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution

Abstract

This paper proposes a new method to measure the pose and localize the contacts with the surrounding environment for an inflatable soft robot by using optical sensors (photocells), inertial measurement units (IMUs), and a pressure sensor. These affordable sensors reside entirely aboard the robot and will be effective in environments where external sensors, such as motion capture, are not feasible to use. The entire bore of the robot is used as a waveguide to transfer the light. When the robot is working, the photocell signals vary with the current shape of the robot and the IMUs measure the orientation of its tip. Analytical functions are developed to relate the photocell signals and the robot pose. Since the soft robot is deformable, the occurrence of contact at any location on its body will modify the sensor signals. This simple measurement approach generates enough information to allow contact events to be detected and classified with high precision using a machine learning algorithm.

Bibliographic Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution

Original language

English

Publication milestones

  • Published - 2023

Publication status

Published - 2023

Publisher

Institute of Electrical and Electronics Engineers Inc.

Publication series

  • Publication series name: 2023 IEEE/SICE International Symposium on System Integration, SII 2023

ISBN (Electronic)

9798350398687

Publication IDs

  • Scopus: 85149143268

Host publication title

2023 IEEE/SICE International Symposium on System Integration, SII 2023