Smart microrobots for mechanical cell characterization and cell convoying.

International audienceThis paper deals with the effective of smart microrobots for both mechanical cell characterization and cell convoying for in vitro fertilization. The first microrobotic device was developed to evaluate oocyte mechanical behavior in order to sort oocytes. A multi-axial micro-force sensor based on a frictionless magnetic bearing was developed. The second microrobotic device presented is a cell convoying device consisting of a wireless micropusher based on magnetic actuation. As wireless capabilities are supported by this microrobotic system, no power supply connections to the micropusher are needed. Preliminary experiments have been performed regarding both cell transporting and biomechanical characterization capabilities under in vitro conditions on human oocytes so as to demonstrate the viability and effectiveness of the proposed setups

Trajectory modelling of a planar magnetic cell micropusher.

International audienceThe improving of the efficiency and the automation of biological cell technologies is a current high stake. One way is to build biological micro-factories which are able to perform a complete biotechnological processes automatically. This technology requires the development of new automatic cell transport system to feed work stations in microfactories. An original magnetic cell micropusher is described in this paper. The ferromagnetic pusher which is submerged in the biological medium follows the movement of a permanent magnet located in the air. This paper focuses on the modelling of the dynamic behaviour of the micropusher in function of the magnet trajectory. The generic model proposed is able to determine pusher trajectory according to the micropusher magnetic properties and the permanent magnet shape and properties. This simulation tool will allow to optimize and to study cell trajectory control in further works

Learning a Tracking Controller for Rolling μ\mubots

Micron-scale robots ($\mu$bots) have recently shown great promise for emerging medical applications. Accurate controlling $\mu$bots, while critical to their successful deployment, is challenging. In this work, we consider the problem of tracking a reference trajectory using a $\mu$bot in the presence of disturbances and uncertainty. The disturbances primarily come from Brownian motion and other environmental phenomena, while the uncertainty originates from errors in the model parameters. We model the $\mu$bot as an uncertain unicycle that is controlled by a global magnetic field. To compensate for disturbances and uncertainties, we develop a nonlinear mismatch controller. We define the model mismatch error as the difference between our model's predicted velocity and the actual velocity of the $\mu$bot. We employ a Gaussian Process to learn the model mismatch error as a function of the applied control input. Then we use a least-squares minimization to select a control action that minimizes the difference between the actual velocity of the $\mu$bot and a reference velocity. We demonstrate the online performance of our joint learning and control algorithm in simulation, where our approach accurately learns the model mismatch and improves tracking performance. We also validate our approach in an experiment and show that certain error metrics are reduced by up to $40\%$.Comment: 8 pages, 9 figure

Modelling of a planar magnetic micropusher for biological cell manipulations.

International audienceThe improving of the efficiency and the automation of biological cell technologies is currently of great importance. One way is to build biological micro-factories which are able to perform complete biotechnological processes automatically. This technology requires the development of new automatic cell transport system to feed work stations in microfactories. An original magnetic cell micropusher is described in this paper. The ferromagnetic pusher which is submerged in the biological medium follows the movement of a permanent magnet located in the air. This paper focuses on the modelling of the dynamic behaviour of the micropusher according to the magnet trajectory. The generic model proposed is able to determine pusher trajectory according to the micropusher magnetic properties and the permanent magnet shape and properties. This simulation tool will permit to optimize and to study cell trajectory control in further works

Actuation, Sensing And Control For Micro Bio Robots

The continuing trend in miniaturization of technology, advancements in micro and nanofabrication and improvements in high-resolution imaging has enabled micro- and meso-scale robots that have many applications. They can be used for micro-assembly, directed drug delivery, microsurgery and high-resolution measurement. In order to create microrobots, microscopic sensors, actuators and controllers are needed. Unique challenges arise when building microscale robots. For inspiration, we look toward highly capable biological organisms, which excel at these length scales. In this dissertation we develop technologies that combine biological components and synthetic components to create actuation, sensing and assembly onboard microrobots. For actuation, we study the dynamics of synthetic micro structures that have been integrated with single-cell biological organisms to provide un-tethered onboard propulsion to the microrobot. For sensing, we integrate synthetically engineered sensor cells to enable a system capable of detecting a change in the local environment, then storing and reporting the information. Furthermore, we develop a bottom-up fabrication method using a macroscopic magnetic robot to direct the assembly of inorganic engineered micro structures. We showcase the capability of this assembly method by demonstrating highly-specified, predictable assembly of microscale building blocks in a semi-autonomous experiment. These magnetic robots can be used to program the assembly of passive building blocks, with the building blocks themselves having the potential to be arbitrarily complex. We extend the magnetic robot actuation work to consider control algorithms for multiple robots by exploiting spatial gradients of magnetic fields. This thesis makes contributions toward actuation, sensing and control of autonomous micro systems and provides technologies that will lead to the development of swarms of microrobots with a suite of manipulation and sensing capabilities working together to sense and modify the environment

Micro/nanoscale magnetic robots for biomedical applications

Magnetic small-scale robots are devices of great potential for the biomedical field because of the several benefits of this method of actuation. Recent work on the development of these devices has seen tremendous innovation and refinement toward ​improved performance for potential clinical applications. This review briefly details recent advancements in small-scale robots used for biomedical applications, covering their design, fabrication, applications, and demonstration of ability, and identifies the gap in studies and the difficulties that have persisted in the optimization of the use of these devices. In addition, alternative biomedical applications are also suggested for some of the technologies that show potential for other functions. This study concludes that although the field of small-scale robot research is highly innovative ​there is need for more concerted efforts to improve functionality and reliability of these devices particularly in clinical applications. Finally, further suggestions are made toward ​the achievement of commercialization for these devices