Generating Optimized Trajectories for Robotic Spray Painting

In the manufacturing industry, spray painting is often an important part of process. Especially in automotive perceived quality final product closely linked to exactness and smoothness For complex products or low batch size production, manual used. But large scale production with a high degree automation, usually performed by industrial robots. There need improve simplify generation robot trajectories used paint booths. A novel method for optimization presented, which can be smooth out generated initial trajectory minimize thickness deviations from target thickness. The smoothed found solving, using interior point solver, continuous non-linear problem. two-dimensional reference function applied selected fitting spline experimental data. This applicator footprint profile then projected geometry as deposition model. After generating trajectory, position duration each segment are variables. primary goal obtain would match when executed. algorithm has been shown produce satisfactory results on both simple 2-dimensional test example, non-trivial case tractor fender. resulting also proven feasible executed robot. Note Practitioners —The work motivated generate well performing robotized spray-painting described applies cases where robotic surface even layer at specified generates optimizes able cover more realistic cases. user it could implemented is, obtained standalone service, but there some prerequisites that fulfilled make use method. It assumed painted available CAD-model physical testing determine characteristics nozzle. These tests amount spraying flat piece material few different distances measuring cross section any handle linear motion commands.