Adaptive Robots for Flexible Manufacturing Systems
Acronym
ARFLEX
Type
research
Duration
2005 - 2008
Content
The project main objectives are to apply the most advanced control technologies (control theory, sensory devices, electronic embedded systems, and, in general, ICT) to radically innovate a class of products – industrial robots – where these technologies did not yet find full applications (the demanding missions have mostly been satisfied by heavy, costly, difficult to reconfigure, mechanical solutions). <br/>The chosen class of products is such that the success of the project will have important impacts not only in that specific class, but on all the manufacturing systems (via its diffusion and substitution potentialities). <br/>The scenario at the base of the project depicts a future of strong changes in many engineering products with an intimate integration of mechanical engineering with electronics, "embedding" into the design the most advanced sw/hw technologies, new intelligent sensors, complex non-linear control theory. <br/>The challenging objective is to overcome the mechanical limitations by embedding the intelligent use of new advanced control system theories supported by the low cost, easy to integrate, electronic and sensors devices. <br/>The robot mission requirements will be met by adding a continuous monitoring of the end tool positioning, feedback for real time control corrections, thus relaxing the requirements on the mechanical parts (accepting limited stiffness in the arms, large imprecision in the coupling joints, and, in general, non-linearity and friction effects). <br/>It will have positive impact on the mission requirements (end tool speed and precision of positioning) and on the cost reduction of the mechanical robot components. <br/>The project aim - to increase flexibility and adaptability, reduce cost and increase the field of applications in the job floor - will be obtained by developing the needed know how and experimental evidence for new generations of high performing embedded control systems for industrial robots in different application contexts.
Funding
6FP IST