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.
trajectory optimization spray painting robot genetic algorithm
LI Fa-zhong ZHAO De-an XIE Gui-hua
School of Electrical and Information Engineering,Jiangsu University,Zhenjiang,Jiangsu,China,212013 School of Civil Engineering and Architecture,Central South University,Changsha,Hunan,China,410075
国际会议
长沙
英文
1851-1854
2009-04-11（万方平台首次上网日期，不代表论文的发表时间）