Precision-Driven Hybrid Control for 3D Microassembly
In recent years, several research groups around the world have demonstrated 3D assembly and manipulation tasks in the micro and nano domain, performed semi-autonomously or autonomously with the help of precision robots. Notable applications include the assembly of MEMS and NEMS sensors and actuators, micro and nano robots, and biological samples. In virtually all cases, research has focused on the feasibility of using top-down automation to perform the required tasks with the required precision. However, the type of control strategy employed in such cases is both part-specific, as well as assembly station specific, and does not take into account important quality factors that are routinely employed macro domain automation. In recent work, we introduced quantitative metrics (the High-Yield Assembly Condition, HYAC), leading to rules for selection of precision robots in microassembly cells (Resolution-Repeatability-Accuracy Rules, RRA). In this presentation, we make use of such metrics and rules to formulate a precision-adjusted hybrid controller. The controller is used as a decision framework to select efficient control strategies during microassembly. We present several benchmark simulation and experimental examples indicating that the use of such a controller can lead to high yields, faster speeds, and to the use of less sensors during top-down automated microassembly.
Webmaster: Micky Rakotondrabe.