Robotics and Biology Laboratory

Robustifying Air-Mass Control of Soft-Pneumatic-Actuators with Air-Flow Sensors

© Posifa


Joel Simon Fuchs
Adrian Sieler
Oliver Brock


The goal of this thesis is to mitigate issues of the current air-mass control strategy of the soft-pneumatic-actuators. So far the controller is derived in a data-driven way and does not rely on accurate sensor-based air-mass estimates. Therefore, when running the controller for a longer time duration, the internal air-mass estimates computed by the model are subject to drift. This results in not being able to control the actuators precisely anymore. In the past years new air-flow-sensors have been developed that might be feasible for our requirements.

Description of work

In the course of this thesis you would evaluate different air-flow sensors and incorporate their characteristics into an air-mass-control-law for the actuators. This control law is then tested in different experiments with the actuators to compare the performance of the previous and the new controller in free-space motion with focus on precision, reaction time and drift.