visual-based approaches measure the force through the displacements or deformation of an elastic micro-structure [193, 194, 195].

Cappelleri et Al. [196] has proposed a force sensing mobile microrobot. This 700 µm² magnetic micro-robot with deformable end-effector uses 2D vision-based tracking template with temporal resolution of 16 fps as force sensor. Barbot et Al. [197] has proposed the uses of a magnetical helical microrobot for force measurements. In such a micro-robots, the rotatory movement is converted into linear movement through interaction with the fluid and the force is proportional to the speed of rotation. Then, by controlling the angular velocity of the robot and by measuring the linear velocity it is possible to apply a controlled force. However, in those reports operating principle is difficult to expand to 3D force measurement, and they non-present any force-controlled manipulation.

Other recent work has considered the contacts between micro-robots and surfaces, where chemical micro-swimmers are guided by topographic paths. These works use the interesting dynamics presented by the Janus catalytically particles when they became close to a surface (bounce off the surface or slide along the surface [198] and have been used to guide the micro-robot along the boundaries [199]. Nevertheless, these responds are passive and do not imply sensing or active control, instead resulting purely from the influence of the external forces on the particle.

Concerning the optical manipulation, photonic force microscopy has been proposed. By moving a trapped probe around a surface of a sample, it is possible to build up an image of its surface in a similar process of the AFM-scanning. The scanning probe can be small spherical particle [200, 201] or micro-sized tool with nano-metric tip [72, 78, 202, 203]. This is a very interesting approach, however it could be further improved by adding closed-loop force control for real time manipulation and exploration tasks in order to increase the ability to interact with rigid and biological objects.

### 4.3.2 Optobots

Optical trapping is a very suitable actuation technique to micro-robots for biomedical and bioengineering applications. Furthermore, they have an intrinsic bio-compatible force transductor, and will be straightforward combined with other strategies with the light as source of energy. Current robotic control research in optical manipulation are focused on the implementation of control techniques based on position. In most of these techniques, direct trapping and manipulation of objects are performed. Some recent works introduce control and planning approach for indirect manipulation of cells using silica beads arranged into gripper formations [204, 84], and we can expect that these techniques can be extended to the control of micro-tool.

None of current robotics techniques exploit the intrinsic force sensing capability of optical trapping. Possibly due to the high dynamic effects in the micro-world
<figure><img src="image_59.png" /><figcaption>Figure 4.12: Working principle of optobots. The light source is separated in multiple independent traps, and used to actuate in 6-DoF a 3D-printed micro-tool for execute precise tasks. Real-time feedback information is used to close the loop and need to be accurate, fast and robust to the micro-world dynamics.</figcaption></figure>

(e.g., quasi instantaneous acceleration) and the limitations in the current detection methods, since the information of the interaction between the robot and its surroundings need to be high-speed, low latency and robust for the environment conditions to be included in a control loop.

Our proposal is to exploit all the capabilities of optical manipulation, and especially its ability to measure the external forces, to create new generation of optical micro-robots capable of interacting with their environment in a controlled and precise manner. Based in our previous contributions, we introduce the so-called "optobots", a mobile micro-robot actuated by optical forces and with an integrated force sensor system. This optobots are micro-robots with 6Dof and a inner build 3D force sensor at more than 1KHz. Fig. 4.12 introduced the working principle and their key elements.

Optobots can be force-controlled in automatic or with haptic feed-back. We believe this new type of micro-robots including the information of 3D external forces would facilitate the 3D navigation and locomotion of the micro-robots, as well as their capabilities to interact with their environment in a controlled and precise manner. In addition, they will provide rich information about the mechanical interactions between cells or objects. This is very valuable for many mechanobiological studies, such as characterizing the stiffness of cell membrane or map the breaking force between moleculas, virus or cells. Thereby, optical micro-robots will create new fields of applications of optical manipulation and extend capabilities of micro-robots in fascinating new ways.
4.3.3 Bilateral Teleoperation of Optical-robot with Force Feedback

As a proof of concept of optical robots with force feedback, a bilateral coupling between our home-built optical trapping platform (ch. 4) and the force sensor (ch. 2) through an haptic interface is realized.

The system allows to control the position of à micro-robot in six dimensions, measure the 3D force in real-time and send this information directly to the user hand via the haptic interface. To validate the optical robots with force-feedback, different experiments in locomotion and manipulation scenarios with Red Blood Cells and synthetic objects are presented next.

<figure><img src="image_60.png" /><figcaption>Figure 4.13: A micro-sphere imitating the behaviour of a bacteria.</figcaption></figure>
4.3.3.1 Most basic optobot: a sphere

First experiment are done with the more basic optical robot, a simple sphere. The experiment consists of imitating the behaviour of a bacteria and is divided into 3 phases. The first is to move the micro-robot freely in each of the three axes, once the contact between the robot and a surface (in this case the glass sheet) is detected thanks to the force feedback, the user blocks the Z axis, and enters in a phase of displacement bordering the surface, in which it has to open path through different obstacles (red blood cells, other polystyrene microspheres and impurities found in the lamella) to finally reach its target, ending in a last phase of interaction with an isolated RBCs.

In the first phase, the micro robot is in free-space, then the movement is dom-
inated by viscous force. This is seen in the plot of the forces (Fig. 4.13.b first
11 sec). When the robot moves in one direction, an opposing force tries to stop
the movement and this force is proportional to the velocity of the micro-robot. To
establish contact between the surface and the robot, the user uses the information
of the force in Z. This detection of the bottom of the petridish is very difficult to
establish without the return of force since the bottom is transparent and cannot be
seen. During the displacement in the plane, bordering the bottom of the Petri-dish,
the force peaks in the axe Z that are seen in the figure 4.13.b are caused by the
impurities that are in the lamella. In this phase, the user moves the sample of
160x100 µm in the plane X,Y in 20 seconds without any knowledge in advance of
the environment, and discovering it gradually, as the camera does not allow him to
see all the work space. Once the target cell is contacted, the contact forces come
into play. Thanks to the force feedback, a correct interaction with the cells can be
easily established.

4.3.3.2 First Optobot prototype

The first prototype of optobots is based on a full disk, which has four optical handles on the extremities for induced the motion and a 3 µm bead in the center. Tracking motions of this bead will be used to extract the force information. As a proof of concept, we use the optobot in a petri-diched with distilled water to come in contact and push some objects find in the bottom of the slide. Figure 4.14 shows part of this experiment. The estimated viscosity force is based on the derivative of the position of the nanostage and consider the optobot as a sphere of 6 µm. The curve hints towards the fact that the force sensor works properly. When the only force to be applied is the viscosity force, the estimated viscosity force matches the 3D measured force. When there are other external forces (like touch the bottom of the petri-dished or pushing objects), the additional force is added to the viscosity force and therefore a gap between the two curves increase.

Initially, the optobot move in each axes, then it stablish contact with a residue
found in the sample, finally it pushing the object applying a force of ~13 pN. Please
note that the hight of the end-effector of this optobot is 300 nm, and without the
force informations is very difficult to find the correct z position to be able to pushing
<figure><img src="image_61.png" /><figcaption>Figure 4.14: First prototype of an optobot. First, the optobot move in *x*, *y* and *z* direction, then it stablish contact with a residue found in the sample, finally it pushing the object.</figcaption></figure>

the tinny object. During the "contact" phase, the end-effector is placed in the same plane of the object using the X force information. When the correct Z positions is known, the optobot is able to easily push the object (T55s to T65s).

This prof-of-concept validate the feasibility of Optobots, Nonetheless, the force information is only reliable in planar motions of the robot, as during the out-of-plane rotations, part of the sphere is covered by the body of the robot. In addition, further investigation in the impact of the actuation and the rigid structure of the robot in the measured force is needed and proper force calibration should be done.

#### 4.3.3.3 Optobots iterations

We propose and 4-pillars robot (cf. Figure 4.15.a). However, in this design the image of the sphere seen via the microscope is very distorted because of the shadows cast by the 4 pillars on the sphere. Fig. 4.15.a shows the ATIS image of the sphere at different axial configurations. It can be expected to use a template tracking algorithm to locate the 3D position, but for practicality and robustness purposes, it is chosen to continue using the algorithm as it was proposed in the chapter 2.
For this reason, and to expands optobots capabilities with 6-Dof an 3D force sensor, it has been proposed single-pillar optobots. Different designs were proposed and manufactured (cf. Figure 4.15.b) to study how the asymmetries in the volume and the surface of the robot affect their stability during rotations and translations. Design differences (e.g. center of mass, size and shape of the end-effector) are likely to impact the performance of the manipulation. However, these studies show qualitative and non quantitative impact. Further investigations in the optimisation of shape and size of optical robots should be done, for example by using simulation software, in order to take advantage of the full potential of optical robots during indirect manipulation tasks.

Nonetheless, these different models allowed us to see that the shape of the robot also have an impact on the fabrication accuracy. Differences in size/shape between design and printing can come from differents effects, as we approach to the 2-pp printed resolution (Nanoscribe, 200 nm).

To understand this differences, it is necessary to take into account the functioning of the 2-pp printing at the software and hardware level. Initially, the software converts the STL file into a print file cutting the STL in slices along the Z axis. The process begins by polymerizing the outline of the object by passing the center of the laser over the contour of the object. During the polymerization process only the focused part of the laser beam will polymerize the resin. The focused laser beam has a voxel shape oriented along the Z axis and will create an overflow related to the thickness of the voxel. The size of the voxel depends on the power of the laser so it is difficult to stablish à precise size of the extra thickness. In addition, the resin shrink during polymerization, and during ageing, by a few percent. Another source of differences, could be in the development process. When the compounds are soaked in the different solvent baths, structures which have a lot of overhangs can be deformed. Also, the evaporation of the solvent will bring stress which can deform the small components.

<figure><img src="image_62.png" /><figcaption>Figure 4.15: (a) Four-pillar Optobot prototype, and the ATIS image with 33 ms accumulation time at differents axial positions. (b) SEM images of diferents designs of the first single-pillar Optobot prototype. (c) Depictions of the final Optobot design with dimensions.</figcaption></figure>
For the optobots, this moves the trapping handles closer to the force sensor than desired. Also, the force sensor is not completely centered with respect to the trapping handles. To solve these problems, it is necessary to design the robot by taking in to account the shrinking of the structure. Also, the spheres should be connected by a straight beam instead of a curved beam as currently. In this way the structures will have a better stiffness against stretching. Fig. 4.15.b depicts the new design of Optobots based on these considerations.

#### 4.3.3.4 Force calibration

The most direct method to determine the stiffness of the trap is to measure the displacement of a trapped object from its equilibrium position in response to the viscous forces produced by the medium, generated by moving the platform with a controlled speed. The drag coefficient has to be known, as the forces arise from the hydrodynamics of the trapped object. This strategy of calibration is known as Drag force method [205].

Different set of experiments were carried out to determine the effective stiffness of the traps in different conditions.

##### 4.3.3.4.1 Multi-trap calibration

First, the stiffness calibration of 3 µm polystyrene beads was performed from 2 to 5 traps at different laser powers. Calibration forces are calculated from Stoke's law in the case of an sphere (Re ~ $10^{-4}$),

$$F_{\text{visc}} = -6\pi\eta r\nu \quad (4.2)$$

where $\nu$ is the velocity, $r$ is the radius of the bead and $\eta$ is the viscosity of the solution. During the calibration process, different traps are created and arranged in a way to have always a trap centered to the event-based camera image. Polystyrene beads are trapped, and constant velocity was applied using velocity command of piezo-controller of the nanostage. The developed algorithm in chapter 2 is used to tracking the 3D motion of this traps. In the calibration routine, the stage was moved in a single axis using linear steps at constant velocities. The velocity is increasing until the trapped bead was displaced by a predetermined distance from its equilibrium position. Then, five cycles at the same velocity are done, and the means of these displacement are used to compute the stiffness according to the equation:

$$F = F_{\text{visc}} = K \cdot (P_{\text{laser}} - P_{\text{probe}}) \quad (4.3)$$

where $P_{\text{laser}} - P_{\text{probe}}$ are the predetermined distance from its equilibrium position of the trap and $K$ is the stiffness of the trap.

Same routine are applied sequentially in the axial and lateral directions. Figure 4.16.a shows the experimental results of the calibration. This routine is performed in real time, directly from the graphical interface. An example of this calibration routine is shown in Fig. 4.16.b.
<figure><img src="image_63.png" /><figcaption>Figure 4.16: (a) Stiffness calibration from 2 to 5 traps at 200Hz with different laser power of 3µm polystyrene beads. The laser power is measured at the output of the laser. (b) Calibration routine of Optobot I with a laser power of 0.5W.</figcaption></figure>

4.3.3.4.2 Optobots Calibration

In order to calibrate the stiffness of Optobots, three different types of Optobots was designed and fabricated (cf. Figure 4.17.(a-c)). Finite element software was used to characterise the hydrodynamics of the trapped object. The laminar fluid flow module from COMSOL Multiphysics is used to solve the drag force of the Optobots in each direction. Results are shown in Fig. 4.17.(d-f). For simplify the integration of the calibration of optobots into our calibration routine, each Optobot is assimilated to an equivalent sphere of radius r for each axis. For Optobot I the corresponding sphere is $r_x=3.92$ µm, $r_y=4.24$ µm and $r_z=5.1062$ µm. For Optobot II the corresponding sphere is $r_x=4.61$ µm, $r_y=5.42$ µm and $r_z=6.08$ µm. And, for Optobot III the corresponding sphere is $r_x=4.47$ µm, $r_y=4.58$ µm and $r_z=5.62$ µm. The stiffness calibration of the Optobots are shown in Fig. 4.17.g. The graph shows that the stiffness of the Optobots is highly superior to the stiffness equivalent to 4
<figure><img src="image_64.png" /><figcaption>Figure 4.17: (a-c) Optical image of different types of Optobots designs. (d-f) Drag force simulation of the three different Optobots in each direction. (g) The stiffness calibration of the Optobots.</figcaption></figure>

individual beads. This may be due to the fact that in physically linked structures such as Optobots, even during the time period when the trap is not active, the object is held by one other trap, contrary to the case of individual beads. With respect to single bead, where the traps are always acting on the sphere, the stiffness in rigid structures is roughly reduced by a factor two.

4.3.3.5 Preliminary experiments

As a preliminary application, bio-compatible 3D Force Microscope Optobot for the topography of cell membranes was designed (cf. Fig. 4.18.b). For preliminary tests, a micro-chip test bench similar to the one that was proposed in chapter 2.3 has also been fabricated (cf. Fig. 4.18.c). The test bench will be used to validate that 3D-FM Optobot allow the mapping of sidewall profile which is very difficult in classical AFM techniques and also to characterise the 3D-FM Optobot resolution. 3D-FM Optobot and micro-chip test bench have been already fabricated and the experiences will be done promptly.

Micro-robots that provide localized mechanical stimulation (e.g. apply piconew-
ton forces perpendicular to the cell membrane for short instants), will be also useful
in the investigation of mechanotransduction in cells, for example their adaptation to
repetitive stimulations and clarify how cells change shape and control their migra-
tory behaviour [206]. Furthermore, Optobots could be used in the characterisations
of cell stiffness in healthy and cancer cells.
<figure><img src="image_65.png" /><figcaption>Figure 4.18: (a) 3D manipulation of a bio-compatible Optobot with force-feedback. (b) Schematic representation of the 3D Force Microscope Optobot for cell membranes topography. (c) Micro-chip test bench for Optobot sidewall characterisation.</figcaption></figure>

We also target different types of force-controlled indirect cells-handling applications, such as isolation, 3D rotation, drug delivery. Base on the results obtained in chapter 2.3, it is expected that optical robots with haptic feedback improves the task performances by a significant margin. We believe that remotely controlled optical robots with force-feedback carry a big potential for future developments in micro-technologies and particularly in cell and molecular biology.
## 4.4 Conclusions

We proposed and experimentally demonstrated a platform for dexterous cell handling through optical manipulation. As a result of an efficient architecture, the manipulation of more than 15 optical traps in a three dimensional workspace with nanometric resolution, is presented. Complex arrangements of optical traps can be grouped and transformed in a variety of ways to achieve diverse tasks. The system provides a straightforward human/machine interaction through a tele-robotic solution allowing dexterous manipulation of synthetic and biological objects in an efficient and intuitive way.

Thanks to its capabilities, and because of the stable and simple set-up design, relevant tasks have been demonstrated in a real biological environment with Red Blood Cells. Besides multiple degrees-of-freedom 3D cells rotation, indirect optical manipulations with 3D printed micro tools were also demonstrated. Furthermore, simultaneous control of several optical robots for collaborative tasks, and the optical micro-assembling of two mobiles pieces have been achieve for the first time. These experiments illustrate the kind of new application that can benefit from the proposed platform.

Possible biological applications include cell sorting, isolation, rotation, stimulation, 3D tomographic imaging, and can contribute to more complex tasks such as single-cell surgeries. In future work, we plan to study the indirect 3D orientation of cells through optical robots with different end-effectors. We anticipate that the 3D micro-manipulation of biological samples without direct exposition to the laser beam will contribute to many cellular applications, where the cell rotation task is a required step, such as nuclear transplantation, embryo micro-injections and polar-body biopsy [207, 208].

We have also introduce the idea of “Optobots”, 3D printing micro-structures actioned by optical tweezers with 6-DoF including a built-in 3D force sensor. As mechanical stress is always present in the cellular environment and mechanotransduction occurs in all cells, this type of optical robot with force measurement will be a formidable instrument for the characterization of biological objects in its own culture medium. We plan to used the optobots to investigate mechanotransduction, and the physical properties of the mechanical stimulus.

Furthermore, force control is important to robust and dexterous manipulation when a manipulator works in a constrained environment. We are also targeting applications as haptic explorations for mapping intracellular elements and any other applications where single cell mechanical stimulation and manipulation are needed.

We plan to extend the 3D force sensing ability for each handle of the robots, allowing a 6D force measurements (multi-axis force/torque sensor) by combining information of each trap. We believe that 6D optical robots with 6D force-feedback will be advantageous for numerous biomedical applications leading micro manipulation to a new level of interaction.
# Conclusions and Future Works

Single cell manipulation and characterisation are considered as a key rising technology in biomedical research. However the lack of intuitive and effective systems make this technology less accessible, limiting its potential. To bridge this critical gap, this thesis has proposed a complete robotic solution for biological manipulation beyond the state-of-the-art limits. The proposed contributions and their future developments are summarized below:

## Real-time 3D force sensing

A new low-latency 3D force measurement method on a trapped object has been developed (cf. chapter 2). It provides picoNewton (pN) resolution with 10 kHz bandwidth. It is compatible with fluorescence, interferential and confocal microscopy and can also be extended to magnetic tweezers and other manipulation techniques. Thanks to their capabilities, 3D haptic optical tweezers system has been implemented. This system provides users with visual information and 3D force feedback, and was proven to consistently improve the users' trajectory tracking and their control of contact forces during manipulation tasks.

Although this experimental force sensor demonstrates the great advantages of using an event-based camera and a dedicated ring algorithm, its performances are very dependent on the light path in which it is used, such as the light-source or the condenser lens. It would be convenient to integrate this system into others optical tweezers systems, or other microscope types such as phase-contrast or in-line microscopes. A possible solution would be to use the event-based camera and machine-learning techniques for the 3D tracking of micro-particles. The idea is to use the 3D actuation system and the events generated at different 3D positions to automatically generate the training data for a supervised learning algorithm, thus adapting to different types of images and systems.

In particular, we plan to expand our force measurement to fluorescent particles by either adapting our tracking algorithm or by proposing a new tracking using deep learning. Adapting the force measurement for fluorescent microscopy will allow different intra-cellular measurements, such as the study of the rheological properties of the nucleus for instance.

## High speed 3D multi-trap actuation

A new actuation method has been proposed to generate and control more than 15 optical traps in 3D with low latency and high bandwidth (cf. chapter 3). The design is solely based on mirrors and very high response times devices, thus maximizing the optical efficiency and the bandwidth of the system. Biological and synthetic objects can be simultaneously manipulated or stimulated. This actuation technique is useful in different applications where the 3D orientation of microscopic objects is needed, such as cell surgery applications, 3D tomographic imaging of living samples,
or micro-assembling in microfluidic devices.

This actuation system is currently limited to a working space of 70 x 50 x 9 µm³ and a scanning frequency of 200Hz. These two limitations restrain the amount of trap that can be created and the working space in which the experiments can be conducted. As a possible solution of this limitations, we propose a new solution to enlarge the actuation workspace by using several "virtual" deformable mirrors in series. The idea is to pass the laser beam several times through the same deformable mirror using a set of mirrors. By ensuring that virtual mirrors are placed on conjugate planes of the entrance aperture of the objective, it is possible to increase the workspace while retaining the quality of traps, at a cost of loss in resolution. If the laser beam is deflected six times through the deformable mirror, the theoretical axial workspace will be 50 µm at 200 Hz or 20µm at 2 kHz. Therefore, this new solution will enlarge the working space, increase the number of traps that can be created and the maximum applicable force. This solution will be implemented and characterized soon.

This 3D actuation system is not only usable for handling particles but for any
application where rapid focusing of a 3-dimensional laser beam is necessary such
as two-photon excitation microscopy, optogenetics and manufacturing by 2-photon
polymerization.

Robotic platform for interactive bio-manipulations

An intuitive tele-robotic with force-feedback platform for single-cell manipulation has been proposed (chapter 4.2). It is implemented with 7-DoF haptic device, allowing dexterous manipulation of synthetic and biological objects. Multi-axis cells rotation, indirect manipulations of cells through optical robots, collaborative tasks, and the optical micro-assembling of two mobiles pieces have been demonstrated.

The next iteration of the platform will be a bio-compatible update. The system will be adapted to the specific needs of the handling of living cells. To this end, we plan to add a stage-up incubator allowing the control of the temperature and the levels of CO2 and O2. A microfluidics device will also be added in order to precisely control inputs and outputs of the chamber and deal with rapid phenomenon occurring when mixing solutions or buffers, for instance when studying the effects of drugs or ligands. In addition, we will implement fluorescence imaging on the system for intra-cellular experiments.

As a future work, we plan the integration of 2-photon polymerization and of
the optical tweezers system using the same multi-trap 3D actuation principle. The
ambition is to use the same system to fabricate and manipulate directly the micro-
structures within the same platform. It will allow the operator to design and print
his own optobots or any micro-structure according to the needs of a given task.
This will not only avoid the difficult task of locating the printed micro-objects after
their development under the manipulation system, but it will also allow the micro-
structures to be printed and simultaneously manipulated (e.g. deformed), opening
the possibility of creating new micro-systems that could not be performed using
other strategies.
Optical robots with force feedback

Optobots, especially printed-design micro-structures with different types of end-
effectors, 6-Dof actuated by optical tweezers and a built-in force sensor has been
presented (chapter 4.3). Optobots are developed to allow biologists to either ma-
nipulate cells while protecting them from prolonged irradiation damage, and for
the characterization of biological objects in their own culture medium. We are
targeting applications such as bio-compatible AFM topography of cell membranes,
the measure of the rigidity and elasticity of the cell surface or intracellular force
transductions, or the mapping of the breaking forces between molecules, viruses or
cells grafted to the optobot with their receptors on the cell surface. Physical and
chemical treatments in Optobots will allow functionalization for more specific tasks
such as pH or temperature sensing. Concerning the structure of the robots, there
is still a great place for optimization of the robot's shape and trap positions, which
could be done using, for instance, simulation tools.

In addition, we plan to measure the 3D force for each handle of robots, thus
allowing a 6D force measurement by combining the information of each trap (force
and moment). These 6-DoF Optobots with a 6D force sensor will allow the study of
new biological interactions, such as the mechanism of Toxoplsama gondii, this latter
requires mechanical work of translation and rotational twisting motion to complete
cellular invasion [209], and therefore only characterizable with a 6D force sensor.

An other very exciting application will be the use of optobots for cell manip-
ulation and characterisation inside living embryos and animals. There are some
examples of cell manipulation on living animals through optical manipulation, but
these are limited to small depths [3] or almost transparent animals such as zebrafish
[210]. The reason is that by focusing the laser on thicker or turbid tissues, the cap-
ture force is significantly reduced by the loss of laser power and the aberrations
introduced at the focal point due to the refractive-index inhomogeneities. It has
been shown that the use of wavefront correction or adaptive optics for aberration
correction is efficient for focusing on turbid media [211]. This has the potential
of achieving optical manipulation at deeper locations within living animals and we
could eventually use the deformable mirror for this task. However, significant in-
vestigations are still necessary.

Multiple 3D force measurement implementation

As a future work, we plan to expand the force measurements capabilities to several
traps. For those purposes, we propose a new solution to perform force measurement
for all traps created by the 3D multi-trap actuation system. This ability is based
on the fact that the actuation system inly uses mirrors, hence the light path is
bidirectional, i.e. the path is independent from the propagation direction. Using
this property and by correctly positioning the sensing system (currently the event-
based camera) we can track the position of the trapped objects by looking at one
trap at a time, wherever its 3D position is, and as the objects are always maintained
in the center of the field of view of the camera.
By synchronizing the multi-trap actuation technique and the event-based cam-
era, it will be possible to differentiate events coming from different traps. This
solution bypasses the problem of determining the center of the mobile laser in a
multi-trap force measurement. However, a trade-off between spatial and temporal
resolution remains, as the totality of pixels is focused in each trapped objects, but
the time to take the measurements depends on the number of created traps and
the scanning frequency. We have a proof-of-concept of this development and are
currently implementing the hardware and software needed to carry it out. This
ability to measure force at multiple locations simultaneously is important in many
biomechanical studies, such as characterizing the stiffness of the membrane of a cell
at multiple points during a fusion phase.

Automatic closed-loop force control

An other perspective of this work, is the automated exploration and control with
force signals. Automated OTs capable of exploring 3D complex environments while
maintaining a predetermined force threshold will allow us to map the topology of
the cell (interior or exterior), while simultaneously measuring stiffness. We plan to
develop a planning method algorithm that uses the OT force sensor information as
a collision detector to construct the topological and mechanical maps.

We will thus be able to map the 3D mechanical interactions between the bead
and subcellular structures, such as intracellular organelles or cytoskeletal fibers,
below a defined force threshold. Automated Optobots capable of exploring in 3D
while controlling the interaction will also be valuable tools for biological applica-
tions. Robots can be functionalized with different compounds and biomolecules and
will allow for instance local and global bond property mapping.

Fully automatic manipulation, even at the macro-scale, remain a great challenge. Mainly due to the need to manipulate all sort of objects not known in advance, according to the task and tools usage, an possibly in contact with their environment or other objects. Thus, we plan to automate task where the users' supervision is not needed, e.g. moving an object to a give location, calibration routines or the indention of a cell with a predetermined force for an given period. We also intend to apply shared-control teleoperation schemes and hybrid control (position and force) in the longer term.

First Use-cases in experimental biology

We plan to demonstrate and validate that such an interactive robotic instrument
is advantageous in a range of use-cases in experimental biology. Collaborative works
with biological partners are planned to produce novel results, focusing on the fields
of cell-to-cell interactions and micro-rheology.

The first use-case to be explored relates to colon cancer, by investigating the
effect of genetic alteration of APC on CD8 T lymphocyte adhesion force to tumoral
cells generating polyps [212]. This work will be done in collaboration with Dr.
Thierry Rose and his group (Lymphocyte Cell Biology Unit at Institut Pasteur).
We will investigate the mechanics of interaction between human CTLs and tumor
cells using optical robots. This biophysical approach will consider the area of the cell-cell interaction and the stiffness of the two membranes in contact, pair by pair, allowing to measure APC and cytoskeleton-dependent mechanical forces during cytotoxicity. The multi-trap actuation allows to roll microbeads independently on the surface of the cell with a calibrated force, and to measure the feedback force exerted by the cell surface for each bead. In this regard, we will map the stiffness over the entire accessible surface of the CTL before, during and after adhesion to the tumor target cell.

The second use-case is related to cell mechanics, where the rheology of the cytoplasm and the nucleus are investigated. This work will be done in collaboration with Dr. Jean-Baptiste Manneville and his group (Molecular mechanisms of intracellular transport Lab' at Institut Curie).

Intracellular mechano-transduction research focuses specifically on forces exerted and transmitted on intracellular components, such as cytoskeletal fibers or intracellular organelles [213]. Since the nucleus is the largest organelle in the cell and is thought to contribute most to cell mechanics, for instance during confined cell migration, we will focus on nuclear mechanics in living cells [59] and on the mechanics of isolated nuclei in vitro (following protocols described in [214]).

The robotic system will be used inside living cells to address currently unresolved questions in intracellular mechanics. Specifically, we will address two questions using this technology: how are forces distributed spatially in 3D and temporally in the cell cytoplasm and how do the mechanical properties of the nucleus differ in living cells and in isolated nuclei in vitro.

## Innovation potential

Manipulating and probing living organism is still a difficult task nowadays and the generalization of such tools will empower scientists and technicians with a new range of possible interactions. The core technology, optical tweezing, is already proven quite useful in biological applications. Additional features especially in interactivity and 3D force spectroscopy are very valuable additions to allow the establishment of novel methods in life science applications. This potential is acknowledged as ISIR laboratory is currently in a maturation process with SATT Lutech<fnref n="1" /> in order to value the different contributions made in this thesis.

The methods developed during this thesis could lead to a product with commercial prospects. There are still steps that should end in a pertinent and innovative modular system, adapted to biology laboratories. The design of compacts modules based on the 3D multi-trap actuation system and 3D multi-trap force measurement systems are required. The modules should be designed to be adapted to diverse existing microscopes, to reach a maximum number of potential partners. The use-cases mentioned above should be used in an incremental design of a mature independent instrument. It will be conceived with an interface and features especially adapted to the workflow of experimental biology.

<footnote n="1">¹Technology Transfer Accelerator Offices, https://www.satt.fr/en/</footnote>
<figure><img src="image_66.png" /></figure>
Publications

Yin, M., **Gerena, E.**, Pacoret, C. and Régnier, S. (2016). Optical tweezers with 3D high speed force feedback. **International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)**, Paris, France.

Yin, M*, **Gerena, E***, Pacoret, C, Haliyo, S and Régnier, S (2017). High-bandwidth 3D Force Feedback Optical Tweezers for Interactive Bio-manipulation. **IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)**, Vancouver, Canada. *Equal contribution. Best Student Paper nominee.

**Gerena, E.**, Régnier, S. and Haliyo, S. (2019). High-bandwidth 3D Multi-Trap Actuation Technique for 6-DoF Real-Time Control of Optical Robots. **IEEE Robotics and Automation Letters**, publisher. Vol 4 No 2 Pages 647 - 654.

**Gerena, E.**, Legendre, F., Vitry, Y., Régnier, S. and Haliyo, S. (2019). Robotic Optical-micromanipulation Platform for Teleoperated Single-Cell Manipulation. **International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)**, Helsinki, Finland. Best Student Paper award.

**Gerena, E.**, Legendre, F., Molawade, A., Vitry, Y., Régnier, S. and Haliyo, S. (2019). Tele-Robotic Platform for Dexterous Optical Single-Cell Manipulation. **Micromachines**. Vol 10 Pages 677.

**Gerena, E.**, Legendre, F., Vitry, Y., Régnier, S. and Haliyo, S. (2020). Improving Optical Micromanipulation with Force-Feedback Bilateral Coupling. **IEEE/RSJ International Conference on Robotics and Automation (ICRA)**, Paris, France.

**Gerena, E.**, Legendre, F., Vitry, Y., Régnier, S. and Haliyo, S. (2020). Optical assembling of untethered micro-robots. **Advanced Optical Materials**, (In preparation).

**Gerena, E.**, Legendre, F., Vitry, Y., Régnier, S. and Haliyo, S. (2020). Force-controlled optical robots for biological manipulations. **Science Robotics**, (In preparation).
<figure><img src="image_67.png" /></figure>
# Appendices
<figure><img src="image_68.png" /></figure>
# Optical Robots Collection
After fabrication of the robots via two-photon polymerisation, they are attached to a glass substrate. For experiments, micro-structures should be collected from the microscope slide and transferred to an another sample chamber. The remaining structures must remain secure on the slide for use in a future experiment.

To solve this problem, a micro-manipulation work-station for robot collection was fabricated. After functional specifications have been defined, the station has been developed during this thesis by intern Akshay Shivaji Nalawade.

## A.1 Setup description

The setup is built around a commercial microscope (OPTIKA). A three-axis micro-manipulator system (MP-285, Sutter Instrument) was implemented in the setup. It provides submicron resolution, and allows fine and coarse positioning of the pipette.

The micro-pipette was fitted to a microliter syringe attached to a manual micro-stage. This stage controls the microliter syringe plunger to collect micro-robots inside the micro-pipette and, subsequently, release them in a other Petri-dish. The suction setup consists of a microliter syringe (Hamilton, 250 µL) mounted on a 3D printed platform and actuated with the help of a manual micro-positioner.

Micro-pipettes (Borosilicate glass capillary, B150-110-10) are fabricated using a micropipette puller from Sutter Instruments (Model P-1000 Flaming Brown Micropipette Puller). The desired micropipette tip size is ~ 40 µm. As micropipette cooker do not allow tip size above 25 µm, micro-pipette was fabricated with glass-on-glass technique. First, the micropipette puller is used to fabricate micropipette with small tip < 2 µm and long taper. Then, another micro-pipette is used to score the glass and make a ~ 40 µm tip with a clean break.

<figure><img src="image_69.png" /><figcaption>Figure A.1: (a) Micro-pipettes fabrication with micro-pipette puller and glass-on-glass technique. (b) Micro-robots collection set-up.</figcaption></figure>
## A.2 Robot collection

For the experiments, the optical robots are removed from the substrate and transferred into a Petri-dish where the trapping experiments will be later performed.

A glass micro-pipette was used at the top of a micro-manipulator to gently remove the selected micro-robots. The motor-driven micromanipulator is used to place the tip of the micropipette near the structures. The optical robots are separated from the substrate one by one with a gentle push of the micro-pipette. Once the robots float freely, they are absorbed and extracted through the pumping action of the syringe via the manual micro-stage.

Then, with the help of the microscope stage, the slide containing the robots is removed, and replaced by a new lamella that contains the objects to be manipulated. Using the motor micro-manipulator, the micropipette is slowly inserted into the new slide. The optical robots are slowly removed from the pipette through a slight flow created from the movement of the manual stage connected to the syringe. When the flow is well controlled, all collected robots are correctly extracted and are close to the desired location. Finally, the Petri-dish is carried to the tele-robotic platform and the different experiments are performed. All the collection procedure was supervised under CMOS camera with a 20X objective lens.

<figure><img src="image_70.png" /><figcaption>Figure A.2: (a) Collection of the robots. (b) Release of the micro-robots.</figcaption></figure>
<figure><img src="image_71.png" /></figure>
# Robot Research Solution
In the previous appendix, a micro-manipulation setup to collect optical robots has been introduced. However, the injection of robots in a sample is still not fully mastered and the position of the robots once injected is not precisely known. In addition, when the experiments are carried out for several days, and the Petri-dish needs to be removed and replaced, the exact location of the robots varies. Therefore, the procedure requires a “Robot Search” phase to find precisely micro-robots positions before starting the main experiment.

When done manually, this search phase is very tedious for the operator. The scale ratio between the sample size (~15 mm diameter) and the observed windows (~70x50 µm) via the user interface makes the research of micro-robots in the sample very long, with sometimes some hours of search. In addition, once placed in the system, the sample is systematically slightly tilted (i.e. not completely horizontal) because of mechanical limitations. Therefore, the focus point may differ of several dozen of micrometres depending on the micro-stage position, meaning that the operator needs to permanently correct the focus, via the z-axis of the nano-stage, while exploring the sample.

As a solution, a software that does this robot search automatically has been developed. After functional specifications has been defined, this software has been developed during this thesis by engineer Florent Legendre.

# B.1 Software description

## B.1.1 Exploration Path

The first step of the robot search automation is to optimize the path followed by the system to sweep completely a designated region of the sample. The operator specifies the area to sweep in “Area to Search” and the program then uses the

<figure><img src="image_72.png" /><figcaption>Figure B.1: Actuators window, allowing to configure the “Focus tracking” function and to control the micro-stage and nano-stage.</figcaption></figure>
micro-stage of the system to explore the designated region.

The area is divided in squares of approximately 1.0x1.0 mm. Each square is then explored following an overlapping spiral path from his center, ensuring a complete sweep of the area without any intervention of the operator. An advantage of the spiral path is that it reduces the focus correction needed because displacements of the micro-stage are smaller than the ones of a linear sweep.

B.1.2 Focus tracking

To solve the focusing issue, a “Focus tracking” function has been developed. Once
this feature is configured and enabled, the program is able to follow the focus swift
over the micro-stage displacements, providing a clean visual feedback without any
focus correction needed from the operator.

In practice, the operator fills focus position value (i.e. the z-axis position of the
nano-stage) of different points around the region to explore in the Actuator window
(cf figure B.1). The software then linearizes the values and create a focus map of
the sample. Once the feature activated, the focus position is evolving according to
the focus map at every change of the micro-stage position.

<figure><img src="image_73.png" /><figcaption>Figure B.2: Image processing window, controlling the Hough Circle function pa-
rameters and the pre-processing of the image before the algorithm.</figcaption></figure>
### B.1.3 Image processing

The final goal of the Robot Search program is to be able to detect micro-robots by himself by directly processing images from the camera during the sweep of the sample.

Micro-robots are discernible from other micro-objects because of their spherical handles used to be controllable by optical tweezers. Those spherical handles can easily be spotted by a circle detection. The disposition of handles allows to distinguish random objects from micro-robots.

To achieve this function, an algorithm based on OpenCV<fnref n="1" /> was developed. Using the “Hough Circle” function, every circle corresponding to the size of optical handles of the micro-robots is found. From this list of circles, the algorithm computes the relative distance between each pair of circles which might correspond to a robot type. Then, the algorithm computes angles formed by pairs of the right length and sharing a circle to compare it with the robot types geometry and form triplets of circles. Finally, those triplets are combined to find robot type patterns. The found robots are added to a list which is then displayed on the user interface.

Robots found positions are listed with the corresponding image of the camera and the degree of confidence of the detection. The operator can then look at the list and confirms if the robot found is valid based on the image. The image processing configuration can be adjusted via the “Image processing” window (cf figure B.2). The operator can modify the parameters of the Hough Circle function as well as the pre-processing (i.e. changing the contrast and luminosity) of the image before the algorithm.

### B.1.4 Robot Types

In order to be able to adapt the system to future micro-robot prototypes, it is possible to dynamically create new "robot type" within the software. Those robot types are used by the algorithm of the image processing to recognize the wanted robot during the exploration (cf subsection "Image processing").

In practice, the operator provides in the Robot type window (cf figure B.3) the relative coordinates of optical handles describing the robot. The model is then automatically drawn and added to the Robot types list.

### B.1.5 Global map

To assist the operator in the conduct of his experiments, a global map is progressively built during the exploration of the sample. The result can be explored in the

<footnote n="1">¹Open Computer Vision Library, https:// opencv.org/</footnote>
<figure><img src="image_74.png" /><figcaption>Figure B.3: Robot type window, allowing the creation of new robot types to search.</figcaption></figure>

"global map window" (cf figure B.4) and saved as png images for further use. The map is created by combining images of the camera according to the coordinates of the actuators.

## B.2 Robot research

To launch a robot search exploration, in the main window, indicate which area to explore and click on the button "Run robot localization" (cf figure B.5). The system should start to explore the area and will list robots found in the main window. Once the exploration is finished, a list of potential robots found is displayed in the main window.

<figure><img src="image_75.png" /><figcaption>Figure B.4: Example of global map resulting of a robot search.</figcaption></figure>
window. The operator needs to look at every element of the list to filter the false positives and find the robot's location.

The software might find a high number of false positive (i.e. list of random objects as robots). The possible high number of false positive require a “robot found validation” phase from the operator. The stricter the circle detection is, the fewer are the false positive, but the higher the chance to miss a robot gets.

<figure><img src="image_76.png" /><figcaption>Figure B.5: Main Window, providing the exploration control and the list of found robots.</figcaption></figure>
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