MiCRoN

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Artist's impression of collaborating micro-robots
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Artist's impression of collaborating micro-robots
Overview of MiCRoN environment
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Overview of MiCRoN environment
Closeup of MiCRoN environment
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Closeup of MiCRoN environment
Gripper imaged with micro-camera
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Gripper imaged with micro-camera
Overview of the MiCRoN microrobot
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Overview of the MiCRoN microrobot
Detection/tracking of micro-gripper and capacitor More videos ...
MiCRoN poster at SHU research seminar
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MiCRoN poster at SHU research seminar
Another picture of the MiCRoN environment
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Another picture of the MiCRoN environment
Table of contents

The MiCRoN Project

Objective

The goal of the European Union IST project MiCRoN (https://cordis.europa.eu/fetch?CALLER=PROJ_IST&ACTION=D&RCN=61495) was the development of a multi-robot manipulation system capable of handling µm-sized objects. The system is based on a small cluster of about a few cubic-centimetre-sized robots. Each robot is equipped with onboard electronics for communications and control. These robots are controlled by infrared communication and they can be equipped with various tools such as syringe-chips, grippers or AFM probes. The aim of the project was to automatically perform tasks like injecting cells with fluids or soldering SMD micro resistors. The project is finished and the MiCRoN public final report is now available (https://vision.eng.shu.ac.uk/jan/MiCRoN-PublicFinalReport-print.pdf)!

Partners

Members from Uppsala (https://www.mst.material.uu.se/), Lausanne (https://microrobotics.epfl.ch/), St. Ingbert (https://www.ibmt.fhg.de/), Athens (https://www.csl.mech.ntua.gr/), Pisa (https://www-mitech.sssup.it/), Barcelona (https://www.ub.es/), Karlsruhe (https://microrobotics.ira.uka.de/) (project-leader), and Sheffield have participated in this project. The task of the Sheffield team was to develop the computer vision software for the MiCRoN project.

Computer Vision

The MiCRoN vision software has to deal with the problem of limited depth of field. Instead of trying to overcome this, one can actually use the depth information concealed in this images to achieve real-time object recognition for microscopes.

By using focus-stacks as models it was possible to provide real-time object recognition of multiple micro-objects in up to 4 degrees-of-freedom. The micro-objects are not required to stay at a fixed distance to the camera any more. Novel automated procedures in biology and micro-technology are thus conceivable.

See Also

External Links

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