Study on Trajectory Optimization of Spray Painting Robot Based on Improved Sparrow Search Algorithm

Authors

• Jie Yang, State Key Laboratory of Digital and Intelligent Technology for Unmanned Coal Mining, Anhui University of Science & Technology, Huainan 232001, China; College of New Energy and Intelligent Connected Vehicle, Anhui University of Science & Technology, Hefei 231131, China
• Zhenkai Xiong, College of New Energy and Intelligent Connected Vehicle, Anhui University of Science & Technology, Hefei 231131, China
• Longyan Wang, EFORT Intelligent Robot Co., Ltd., Wuhu 241060, China

Abstract

Abstract: To address the challenges posed by the complex working environment to the trajectory planning of the spray painting robot, a multi-strategy integrated sparrow search algorithm (MISSA) was proposed with the dual optimization objectives of time efficiency and motion smoothness. The 3-5-3 polynomial interpolation method was adopted to design the trajectory curve, aiming to ensure continuous angular displacement, angular velocity, and angular acceleration throughout the process. A multidimensional optimization problem with joint constraints was constructed using the total trajectory duration as the performance index. MISSA, which integrates refraction reverse learning, sine-cosine adaptive adjustment, and Cauchy mutation, was utilized to optimize the time parameters of interpolation nodes to achieve time minimization. The simulation results show that MISSA outperforms the ISSA, SSA, PSO, and GWO algorithms on 12 typical test functions, demonstrating stronger global search ability and higher convergence accuracy. The trajectory optimization experiment shows that the trajectory time is shortened from 12 s to 5.515 5 s after optimization; the efficiency is improved by 54.04%, and the motion curves of all joints are smooth, meeting engineering constraints. Actual measurements by a laser tracker verify that the straight-line trajectory repeatability RP of the robot at a speed of 1 600 mm/s is only 0.177 mm, which meets the requirements for high-precision operations, thus verifying the engineering applicability and robustness of the algorithm.

Recommended Citation

Yang, Jie; Xiong, Zhenkai; and Wang, Longyan (2026) "Study on Trajectory Optimization of Spray Painting Robot Based on Improved Sparrow Search Algorithm," Journal of System Simulation: Vol. 38: Iss. 7, Article 13.
DOI: 10.16182/j.issn1004731x.joss.25-0756
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss7/13

First Page

1978

Last Page

1992

CLC

TP242.2; TP391.9

Recommended Citation

Yang Jie, Xiong Zhenkai, Wang Longyan. Study on Trajectory Optimization of Spray Painting Robot Based on Improved Sparrow Search Algorithm[J]. Journal of System Simulation, 2026, 38(7): 1978-1992.

Corresponding Author

Xiong Zhenkai

DOI

10.16182/j.issn1004731x.joss.25-0756