Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators

Abstract

This paper presents a vision-based sensing approach for a soft linear actuator, which is equipped with an integrated camera. The proposed vision-based sensing pipeline predicts the three-dimensional position of a point of interest on the actuator. To train and evaluate the algorithm, predictions are compared to ground truth data from an external motion capture system. An off-the-shelf distance sensor is integrated in a similar actuator and its performance is used as a baseline for comparison. The resulting sensing pipeline runs at 40 Hz in real-time on a standard laptop and is additionally used for closed loop elongation control of the actuator. It is shown that the approach can achieve comparable accuracy to the distance sensor.

This work has been submitted to the 2020 IEEE International Conference on Robotics and Automation (ICRA) for possible publication. Accompanying video: https://youtu.be/1MJuhxVcTns