Haptic feedback in teleoperation in Micro-and Nano-Worlds.

International audienceRobotic systems have been developed to handle very small objects, but their use remains complex and necessitates long-duration training. Simulators, such as molecular simulators, can provide access to large amounts of raw data, but only highly trained users can interpret the results of such systems. Haptic feedback in teleoperation, which provides force-feedback to an operator, appears to be a promising solution for interaction with such systems, as it allows intuitiveness and flexibility. However several issues arise while implementing teleoperation schemes at the micro-nanoscale, owing to complex force-fields that must be transmitted to users, and scaling differences between the haptic device and the manipulated objects. Major advances in such technology have been made in recent years. This chapter reviews the main systems in this area and highlights how some fundamental issues in teleoperation for micro- and nano-scale applications have been addressed. The chapter considers three types of teleoperation, including: (1) direct (manipulation of real objects); (2) virtual (use of simulators); and (3) augmented (combining real robotic systems and simulators). Remaining issues that must be addressed for further advances in teleoperation for micro-nanoworlds are also discussed, including: (1) comprehension of phenomena that dictate very small object (< 500 micrometers) behavior; and (2) design of intuitive 3-D manipulation systems. Design guidelines to realize an intuitive haptic feedback teleoperation system at the micro-nanoscale level are proposed

Semi-autonomous scheme for pushing micro-objects

-In many microassembly applications, it is often desirable to position and orient polygonal micro-objects lying on a planar surface. Pushing micro-objects using point contact provides more flexibility and less complexity compared to pick and place operation. Due to the fact that in micro-world surface forces are much more dominant than inertial forces and these forces are distributed unevenly, pushing through the center of mass of the micro-object will not yield a pure translational motion. In order to translate a micro-object, the line of pushing should pass through the center of friction. In this paper, a semi-autonomous scheme based on hybrid vision/force feedback is proposed to push microobjects with human assistance using a custom built telemicromanipulation setup to achieve pure translational motion. The pushing operation is divided into two concurrent processes: In one process human operator who acts as an impedance controller alters the velocity of the pusher while in contact with the micro-object through scaled bilateral teleoperation with force feedback. In the other process, the desired line of pushing for the micro-object is determined continuously using visual feedback procedures so that it always passes through the varying center of friction. Experimental results are demonstrated to prove nanoNewton range force sensing, scaled bilateral teleoperation with force feedback and pushing microobjects

Force feedback pushing scheme for micromanipulation applications

Pushing micro-objects using point contact provides more flexibility and less complexity compared to pick and place operation. Due to the fact that in micro-world surface forces are much more dominant than inertial forces and these forces are distributed unevenly, pushing through the center of mass of the micro-object may not yield a pure translational motion. In order to translate a micro-object, the line of pushing should pass through the center of friction. In this paper, a semi-autonomous scheme based on hybrid vision/force feedback procedure is proposed to push micro-objects with human assistance using a custom built tele-micromanipulation setup to achieve translational motion. In the semi-autonomous pushing process, velocity controlled pushing with force feedback is realized along x-axis by the human operator while y-axis orientation is undertaken automatically using visual feedback. This way the desired line of pushing for the micro-object is controlled to pass through the varying center of friction. Experimental results are shown to prove nano-Newton range force sensing, scaled bilateral teleoperation with force feedback and snapshot of pushing operation

Additive nanomanufacturing: a review

Additive manufacturing has provided a pathway for inexpensive and flexible manufacturing of specialized components and one-off parts. At the nanoscale, such techniques are less ubiquitous. Manufacturing at the nanoscale is dominated by lithography tools that are too expensive for small- and medium-sized enterprises (SMEs) to invest in. Additive nanomanufacturing (ANM) empowers smaller facilities to design, create, and manufacture on their own while providing a wider material selection and flexible design. This is especially important as nanomanufacturing thus far is largely constrained to 2-dimensional patterning techniques and being able to manufacture in 3-dimensions could open up new concepts. In this review, we outline the state-of-the-art within ANM technologies such as electrohydrodynamic jet printing, dip-pen lithography, direct laser writing, and several single particle placement methods such as optical tweezers and electrokinetic nanomanipulation. The ANM technologies are compared in terms of deposition speed, resolution, and material selection and finally the future prospects of ANM are discussed. This review is up-to-date until April 2014

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

Vision-based haptic feedback for remote micromanipulation in-SEM environment.

International audienceThis paper presents an intuitive environment for remote micromanipulation composed of both haptic feedback and virtual reconstruction of the scene. To enable non expert users to perform complex teleoperated micromanipulation tasks it is of utmost importance to provide them with information about the 3D relative positions of the objects and the tools. Haptic feedback is an intuitive way to transmit such information. Since position sensors are not available at this scale, visual feedback is used to derive information about the scene. In this work, three different techniques are implemented, evaluated and compared to derive the object positions from scanning electron microscope images. The modified correlation matching with generated template algorithm is accurate and provides reliable detection of objects. To track the tool, a marker based approach is chosen since fast detection is required for stable haptic feedback. Information derived from these algorithms is used to propose an intuitive remote manipulation system, that enables users situated in geographically distant sites to benefit from specific equipments such as SEMs. Stability of the haptic feedback is ensured by the minimization of the delays, the computational efficiency of vision algorithms and the proper tuning of the haptic coupling. Virtual guides are proposed to avoid any involuntary collisions between the tool and the objects. This approach is validated by a teleoperation involving melamine microspheres with a diameter of less than 2 m between Paris, France and Oldenburg, Germany