Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators
This work addresses proprioceptive sensing for soft robotics, enabling closed-loop control, but it is incremental as it adapts existing vision methods to a specific actuator type.
The paper tackles the problem of sensing the 3D position of a soft linear actuator by developing a vision-based pipeline using an integrated camera, achieving real-time performance at 40 Hz and accuracy comparable to a distance sensor baseline.
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.