Kinematics parameters estimation for an AFM/Robot integrated micro-force measurement system.

International audienceThis paper introduces a novel atomic force microscope (AFM) and parallel robot integrated micro-force measurement system whose objective is the measurement of adhesion force between planar micro-objects. This paper is mainly focused on the kinematics parameters estimation between the objects to be measured, the parallel robot and the AFM system in order to position both objects during measurement. A substrate is placed on the end-platform of the parallel robot system, on which three markers are utilized as the reference information to the kinematics parameters estimation. The markers are identified by the AFM scanning in order to identify the kinematics parameters of the whole system. Based on the classic Gauss-Newton algorithm, the position and orientation can be solved. Finally, the effectiveness of the proposed method is demonstrated through the experiments on the prototype of the micro-force measurement system. The parameters estimation methodology outlined is generic and also can be extended to a variety of applications in calibration of micro-robots

Proceedings of the 4th International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME2018)

The Mechatronics Department (Accredited by National Board of Accreditation, New Delhi, India) of the G H Patel College of Engineering and Technology, Gujarat, India arranged the 4th International Conference on Innovations in Automation and Mechatronics Engineering 2018, (ICIAME 2018) on 2-3 February 2018. The papers presented during the conference were based on Automation, Optimization, Computer Aided Design and Manufacturing, Nanotechnology, Solar Energy etc and are featured in this book

MICROCANTILEVER-BASED FORCE SENSING, CONTROL AND IMAGING

This dissertation presents a distributed-parameters base modeling framework for microcantilever (MC)-based force sensing and control with applications to nanomanipulation and imaging. Due to the widespread applications of MCs in nanoscale force sensing or atomic force microscopy with nano-Newton to pico-Newton force measurement requirements, precise modeling of the involved MCs is essential. Along this line, a distributed-parameters modeling framework is proposed which is followed by a modified robust controller with perturbation estimation to target the problem of delay in nanoscale imaging and manipulation. It is shown that the proposed nonlinear model-based controller can stabilize such nanomanipulation process in a very short time compared to available conventional methods. Such modeling and control development could pave the pathway towards MC-based manipulation and positioning. The first application of the MC-based (a piezoresistive MC) force sensors in this dissertation includes MC-based mass sensing with applications to biological species detection. MC-based sensing has recently attracted extensive interest in many chemical and biological applications due to its sensitivity, extreme applicability and low cost. By measuring the stiffness of MCs experimentally, the effect of adsorption of target molecules can be quantified. To measure MC\u27s stiffness, an in-house nanoscale force sensing setup is designed and fabricated which utilizes a piezoresistive MC to measure the force acting on the MC\u27s tip with nano-Newton resolution. In the second application, the proposed MC-based force sensor is utilized to achieve a fast-scan laser-free Atomic Force Microscopy (AFM). Tracking control of piezoelectric actuators in various applications including scanning probe microscopes is limited by sudden step discontinuities within time-varying continuous trajectories. For this, a switching control strategy is proposed for effective tracking of such discontinuous trajectories. A new spiral path planning is also proposed here which improves scanning rate of the AFM. Implementation of the proposed modeling and controller in a laser-free AFM setup yields high quality image of surfaces with stepped topographies at frequencies up to 30 Hz. As the last application of the MC-based force sensors, a nanomanipulator named here MM3A® is utilized for nanomanipulation purposes. The area of control and manipulation at the nanoscale has recently received widespread attention in different technologies such as fabricating electronic chipsets, testing and assembly of MEMS and NEMS, micro-injection and manipulation of chromosomes and genes. To overcome the lack of position sensor on this particular manipulator, a fused vision force feedback robust controller is proposed. The effects of utilization of the image and force feedbacks are individually discussed and analyzed for use in the developed fused vision force feedback control framework in order to achieve ultra precise positioning and optimal performance

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

Wide Range Control and Performance Evaluation of a Single-Axis Compliant Nano-Positioning System

This thesis is focused on the development of compliant nano-positioning system. The mechanical design is presented and each component is thoroughly described. The control algorithm developed is based on a PID feedback position control and a force feedforward control. This thesis focuses on 3 achievements. First, improvement of the closed-loop control taking into account the nonlinearities. Secondly, the dynamic behavior has been analyzed. Finally, the cross-axis coupling has been examined

Engineering for a changing world: 60th Ilmenau Scientific Colloquium, Technische Universität Ilmenau, September 04-08, 2023 : programme

In 2023, the Ilmenau Scientific Colloquium is once more organised by the Department of Mechanical Engineering. The title of this year’s conference “Engineering for a Changing World” refers to limited natural resources of our planet, to massive changes in cooperation between continents, countries, institutions and people – enabled by the increased implementation of information technology as the probably most dominant driver in many fields. The Colloquium, supplemented by workshops, is characterised but not limited to the following topics: – Precision engineering and measurement technology Nanofabrication – Industry 4.0 and digitalisation in mechanical engineering – Mechatronics, biomechatronics and mechanism technology – Systems engineering – Productive teaming - Human-machine collaboration in the production environment The topics are oriented on key strategic aspects of research and teaching in Mechanical Engineering at our university

Software framework for high precision motion control applications

Developing a motion control system requires much effort in different domains. Namely control, electronics and software engineering. In addition to these, there are the system requirements which may be completely different to these spanning from biomedical engineering to psychology. Collaboration between these fields is vital, however these fields should be involved only as much as they are needed to be in the fields of expertise of the others. Several software frameworks exist for the creation of robotics applications. But currently there is no standard for the creation of mechatronics systems nor is there a complete software package that can deal with all aspects in the programming of such systems. Existing frameworks each have their advantages and disadvantages, however they generally have limited or no dedicated structure for the development of the motion control aspect of the problem and deal extensively with the robotenvironment interactions and inter mechanism communications. Dealing with the higher levels of the problem, they are usually not well suited for hard realtime; since the interactions can run on soft realtime constraints. The software framework proposed in this study aims to achieve a level of abstraction between the different domains utilized within a system. The aim in using the framework is to achieve a sustainable software structure for the system. Sustainability is an important part of systems, as it permits a system to evolve with changing requirements and variable hardware, with the ultimate goal of having robust software that can be utilized on different platforms and with other systems using an abstraction layer between the hardware and the software. This ensures that the system can be migrated from a processing platform to any other platform and also from one set of hardware to another. The framework was tested on several systems that have precision motion control requirements such as a 10 degree of freedom micro assembly workstation, a modular micro factory and a haptic system with time delay. Each of the systems works in di erent processing platforms and have different motion control requirements. The achieved results from the implementations show that the software framework is an important tool for the development of motion control software

Modeling and experimental validation of a parallel microrobot for biomanipulation

The main purpose of this project is the development of a commercial micropositioner's (SmarPod 115.25, SmarAct GmbH) geometrical model. SmarPod is characterized by parallel kinematics and is employed for precise and accurate sample's positioning under SEM microscope, being vacuum-compatible, for various applications. Geometrical modeling represents the preliminar step to fully understand, and possibly improve, robot's closed loop behaviour in terms of task's quality precision, when enterprises does not provide sufficient documentation. The robotic system, in fact, represents in this case a "black box" from which it's possible to extract information. This step is essential in order to improve, consequently, the reliability of bio-microsystem manipulation and characterization. Disposing of a detailed microrobot's model becomes essential to deal with the typical lack of sensing at microscale, as it allows a 3D precise and adequate reconstruction, realized through proper softwares, of the manipulation set-up. The roles of Virtual Reality (VR) and of simulations, carried out, in this case, in Blender environment, are asserted as well as an essential helping tool in mycrosystem's task planning. Blender is a professional free and open-source 3D computer graphics software and it is proven to be a basic instrument to validate microrobot's model, even to simplify it in case of complex system's geometries

3D reconstruction, classification and mechanical characterization of microstructures

Modeling and classifying 3D microstructures are important steps in precise micro-manipulation. This thesis explores some of the visual reconstruction and classification algorithms for 3D microstructures used in micromanipulation. Mechanical characterization of microstructures has also been considered. In particular, visual reconstruction algorithm (shape from focus - SFF) uses 2D image sequence of a microscopic object captured at different focusing levels to create a 3D range image. Then, the visual classification algorithm takes the range image as an input and applies a curvature-based segmentation method, HK segmentation, which is based on differential geometry. The object is segmented into surface patches according to the curvature of its surface. It is shown that the visual reconstruction algorithm works successfully for synthetic and real image data. The range images are used to classify the surfaces of the micro objects according to their curvatures in the HK segmentation algorithm. Also, a mechanical property characterization technique for cell and embryo is presented. A zebrafish embryo chorion is mechanically characterized using cell boundary deformation. Elastic modulus and developmental stage of the embryo are obtained successfully using visual information. In addition to these, calibrated image based visual servoing algorithm is experimentally evaluated for various tasks in micro domain. Experimental results on optical system calibration and image-based visual servoing in micropositioning and trajectory following tasks are presented