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

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.