Trajectory Optimization of Spray Painting Robot Based on Adapted Genetic Algorithm

Due to the complex geometry of free-form surfaces, generating optimization trajectories of spray gun to satisfy paint uniformity requirement is still a challenge. A quadratic function of the paint deposition rate on a plane was proposed according to the experimental data, and a model of paint deposition rate on a free-form surface was established. Non-uniform paint deposition in the direction of the Tool Center Point(TCP) passes on non-planar surfaces is resulted from the change of curvature along the pass. The model of variable spray speed optimization was established to compensate for the curvature change and improve the uniformity of paint deposition along passes. Then a new genetic algorithm (GA) for speed optimization was presented with good convergence properties and a remarkable low computational load. Finally, a typical concavo-convex surface was chosen as a target surface to validate the performance of the proposed algorithms, and the simulation results show that the algorithms can be applied substantially to improve the uniformity of resultant paint deposition along the passes.