Modeling, simulation and control of microrobots for the microfactory.

Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large quantities of components, and the high cost associated with top-down manipulation requiring precision. However, bottom-up manufacturing methods have certain limitations, such as components needing to have predefined shapes and surface coatings, and the number of assembly components being limited to very few. For example, in the case of self-assembly of nano-cubes with an origami design, post-assembly manipulation of cubes in large quantities and cost-efficiency is still challenging. In this thesis, we envision a new paradigm for nanoscale assembly, realized with the help of a wafer-scale microfactory containing large numbers of MEMS microrobots. These robots will work together to enhance the throughput of the factory, while their cost will be reduced when compared to conventional nanopositioners. To fulfill the microfactory vision, numerous challenges related to design, power, control, and nanoscale task completion by these microrobots must be overcome. In this work, we study two classes of microrobots for the microfactory: stationary microrobots and mobile microrobots. For the stationary microrobots in our microfactory application, we have designed and modeled two different types of microrobots, the AFAM (Articulated Four Axes Microrobot) and the SolarPede. The AFAM is a millimeter-size robotic arm working as a nanomanipulator for nanoparticles with four degrees of freedom, while the SolarPede is a light-powered centimeter-size robotic conveyor in the microfactory. For mobile microrobots, we have introduced the world’s first laser-driven micrometer-size locomotor in dry environments, called ChevBot to prove the concept of the motion mechanism. The ChevBot is fabricated using MEMS technology in the cleanroom, following a microassembly step. We showed that it can perform locomotion with pulsed laser energy on a dry surface. Based on the knowledge gained with the ChevBot, we refined tits fabrication process to remove the assembly step and increase its reliability. We designed and fabricated a steerable microrobot, the SerpenBot, in order to achieve controllable behavior with the guidance of a laser beam. Through modeling and experimental study of the characteristics of this type of microrobot, we proposed and validated a new type of deep learning controller, the PID-Bayes neural network controller. The experiments showed that the SerpenBot can achieve closed-loop autonomous operation on a dry substrate

Vision Based Automatic Calibration of Microrobotic System

During the last decade, the advancement of microrobotics has provided a powerful tool for micromanipulation in various fields including living cell manipulation, MEMS/MOEMS assembly, and micro-/nanoscale material characterization. Several dexterous micromanipulation systems have been developed and demonstrated. Nowadays, the research on micromanipulation has shifted the scope from the conceptual system development to the industrial applications. Consequently, the future development of this field lies on the industrial applicability of systems that aims to convert the micromanipulation technique to the mass manufacturing process. In order to achieve this goal, the automatic microrobotic system, as the core in the process chain, plays a significant role. This thesis focuses on the calibration procedure of the positioning control, which is one of the fundamental issues during the automatic microrobotic system development. A novel vision based procedure for three dimensional (3D) calibrations of micromanipulators is proposed. Two major issues in the proposed calibration approach - vision system calibration and manipulator kinematic calibration - are investigated in details in this thesis. For the stereo vision measurement system, the calibration principle and algorithm are presented. Additionally, the manipulator kinematic calibration is carried out in four steps: kinematic modeling, data acquisition, parameter estimation, and compensation implementation. The procedures are presented with two typical models: the matrix model and the polynomial model. Finally, verification and evaluation experiments are conducted on the microrobotic fiber characterization platform in the Micro- and Nano Systems Research Group (MST) at Tampere University of Technology. The results demonstrate that the proposed calibration models are able to reduce the prediction error below 2.59 micrometers. With those models, the pose error, compensated by the feed-forward compensator, can be reduced to be smaller than 5 µm. The proposed approach also demonstrates the feasibility in calibrating the decoupled motions, by reducing the undesired movement from 28 µm to 8 µm (For 4800 µm desired movement)