Automatic pick-and-place of 40 microns objects using a robotic platform.

International audienceRobotic micro-assembly is one way to manufacture new generation of out of plane and/or hybrid microsystems. This approach requires the study of micromanipulation strategies adapted to the microworld and especially to the surface and adhesion forces. We are focusing our works on the study of robotic assembly methods applied to objects whose size is below 100 micrometers. The handling strategy used is based on a two fingered gripper. In order to reduce the adhesion between the gripper and the manipulated objects specific end-effectors have been developed. Moreover, to improve the release reliability we are using a polymer substrate which induces high adhesion with the objet. Some automatic pick-and-places on objects whose typical size is 40 micrometers have been done (cycle time of 1.8 second). There show the reliability of the proposed approach

Novel estimation and control techniques in micromanipulation using vision and force feedback

With the recent advances in the fields of micro and nanotechnology, there has been growing interest for complex micromanipulation and microassembly strategies. Despite the fact that many commercially available micro devices such as the key components in automobile airbags, ink-jet printers and projection display systems are currently produced in a batch technique with little assembly, many other products such as read/write heads for hard disks and fiber optics assemblies require flexible precision assemblies. Furthermore, many biological micromanipulations such as invitro-fertilization, cell characterization and treatment rely on the ability of human operators. Requirement of high-precision, repeatable and financially viable operations in these tasks has given rise to the elimination of direct human involvement, and autonomy in micromanipulation and microassembly. In this thesis, a fully automated dexterous micromanipulation strategy based on vision and force feedback is developed. More specifically, a robust vision based control architecture is proposed and implemented to compensate errors due to the uncertainties about the position, behavior and shape of the microobjects to be manipulated. Moreover, novel estimators are designed to identify the system and to characterize the mechanical properties of the biological structures through a synthesis of concepts from the computer vision, estimation and control theory. Estimated mechanical parameters are utilized to reconstruct the imposed force on a biomembrane and to provide the adequate information to control the position, velocity and acceleration of the probe without damaging the cell/tissue during an injection task