Machine vision methods for autonomous micro‐robotic systems

Abstract

Purpose

To develop customised machine vision methods for closed‐loop micro‐robotic control systems. The micro‐robots have applications in areas that require micro‐manipulation and micro‐assembly in the micron and sub‐micron range.

Design/methodology/approach

Several novel techniques have been developed to perform calibration, object recognition and object tracking in real‐time under a customised high‐magnification camera system. These new methods combine statistical, neural and morphological approaches.

Findings

An in‐depth view of the machine vision sub‐system that was designed for the European MiCRoN project (project no. IST‐2001‐33567) is provided. The issue of cooperation arises when several robots with a variety of on‐board tools are placed in the working environment. By combining multiple vision methods, the information obtained can be used effectively to guide the robots in achieving the pre‐planned tasks.

Research limitations/implications

Some of these techniques were developed for micro‐vision but could be extended to macro‐vision. The techniques developed here are robust to noise and occlusion so they can be applied to a variety of macro‐vision areas suffering from similar limitations.

Practical implications

The work here will expand the use of micro‐robots as tools to manipulate and assemble objects and devices in the micron range. It is foreseen that, as the requirement for micro‐manufacturing increases, techniques like those developed in this paper will play an important role for industrial automation.

Originality/value

This paper extends the use of machine vision methods into the micron range.

Citation

Amavasai, B.P., Caparrelli, F., Selvan, A., Boissenin, M., Travis, J.R. and Meikle, S. (2005), "Machine vision methods for autonomous micro‐robotic systems", Kybernetes, Vol. 34 No. 9/10, pp. 1421-1439. https://doi.org/10.1108/03684920510614740