Realtime vision based dynamic power management of in-plane magnetic mobile microrobots for avoidance of excessive surface stiction

Abstract

Mobile microrobots can be used as on-chip remote micromanipulation tools to handle with delicate samples, such as cells and biological tissues. Many efforts have been made to improve microrobots actuation, controllability and power consumption. However, stiction phenomena occurring between the robot and the substrate on which it is moving are still a big issue to deal with. In this paper stiction problem is addressed with a new approach. To begin, the two contact surfaces are coated with low friction materials combination (Al2O3/Si3N4) and different roughnesses are taken into account, in order to find the best combination and to ensure uniform sample conditions. Tests have been made, proving that a rough bottom surface of microrobots moving on a Si3N4 coated glass substrate minimizes stiction events. Starting from this surface combination, the powering algorithm of the electromagnetic field generation system is changed: oscillations perpendicular to the robot trajectory are added to the standard actuation power to overcome static friction while parallel ones are used to avoid dynamic friction, which speeds down the robot. The new powering algorithm is adapted in realtime by visually tracked position and speed of the microrobots. Both the fabrication process flow and the powering algorithm are fully described in the paper. Coatings and adaptive powering show promising results: they manage to reach a long time closed-loop position control stability of the microrobot and they can be applied to find the smoothest path between two points after having performed a surface scanning to map the in-plane stiction distributions. Enhanced position control accuracy and the demonstrated robustness in long term motion control through the proposed approaches could be an important asset to on-chip microrobots toward their biological or micromanufacturing applications.