Abstract:
Geometrically complex structural components are extensively used in the assembly of
airframe structures. Currently the application of robotics to the assembly of such
structures has been limited and the assembly of aero-structure components is primarily a
skilled manual process. The use of manual handling represents a significant health and
safety risk and an increased likelihood of damaging components during the assembly
process. The compliance of components is significant and the resulting geometric and
positional uncertainty within the assembly is such that conventional robotic pick and
place approaches cannot be used as it is impossible to pre-define and fix the exact
position of parts within the assembly. Using product specific fixtures and templates can
solve this problem, but this significantly increases cost and reduces flexibility. This
paper addresses the above problems by using a novel combination of standard low cost
industrial robots, low cost sensors and a mathematical ‘best-fit’ algorithm. During the
assembly process the location of existing part-to-part holes and edges are measured to
provide alignment points for individual components within the structure and the data
obtained is processed through a ‘best-fit’ mathematical algorithm to calculate the
relative component positions required for an optimal assembly. The developed
methodology has been evaluated and demonstrated using real airframe components and
results are presented. The assembly experiments presented have confirmed that it is
possible to assemble aero-structure components within aerospace production
specifications.
