Spot-welding path planning method for the curved surface workpiece of body-in-white based on a memetic algorithm

Abstract

Aiming at the problem of complex path planning in the processing of curved surface workpieces of body-in-white, a hybrid path planning method based on memetic algorithm is proposed. The method is divided into two parts, welding sequence planning and welding path planning between welding joints. By establishing the kinematics model of spot welding robot based on pipper criterion and z-y-z Euler angle solution method, the motion constraints of path optimization are analyzed. Under the framework of the memetic algorithm, the improved A-star algorithm with redundant node deletion and post smoothing process is used to obtain the smooth collision-free optimal path set between welding joints, and construct the objective function of traveling all welding joints with the shortest path length and the highest smoothness, the multi-objective elitist simulated annealing genetic algorithm is used to achieve the welding sequence planning of all welding joints. The variable neighborhood search method improves the mutation operator, the elitist strategy is introduced to improve the probability of crossover and mutation operation, and a simulated annealing algorithm is used to jump out of local search to get the global optimal solution. According to the motion constraints, the joint space path is obtained by the optimal path in Cartesian space. Simulations analysis results demonstrate that the hybrid path planning method based on the memetic algorithm can effectively optimize the path of spot welding robot, lay the foundation of controlling and trajectory planning during welding processes.

Review of path planning of welding robot based on spline curve

“…It constructs an objective function for traversing all solder joints with the shortest path length and the highest smoothness. Simulation results demonstrate the effectiveness of the hybrid path planning method based on the meme algorithm in optimizing the path of a spot welding robot [69]. MA is primarily applied to combinatorial optimization problems (such as the Traveling Salesman Problem (TSP) and the boxing problem), continuous optimization problems (including parameter optimization and function optimization), and model tuning problems.…”

Global Path Planning for Differential Drive Mobile Robots Based on Improved BSGA* Algorithm

“…There are mainly three heuristic functions, in-cluding Euclidean distance function [34], Chebyshev distance function [35], and Manhattan distance function [36]. They can be expressed, respectively, as follows:…”

“…2023, 13, x FOR PEER REVIEW 6 of 24 45°, −45°, 90°, −90°, 135°, −135°, 180°). There are mainly three heuristic functions, including Euclidean distance function [34], Chebyshev distance function [35], and Manhattan distance function [36]. They can be expressed, respectively, as follows: Euclidean distance function:…”

Welding motion matching of tank with variable curvature section based on discrete planning method of welding torch posture

“…For the issue of complex curve path planning, it is an effective method to develop and improve the algorithm [14][15][16][17][18][19]. Xiao et al [14] and Lv et al [15] used a novel high-priority subregion searching algorithm and improved equal chord height error algorithm respectively for the problem of polishing path planning and intelligent planning of grinding and polishing path.…”

“…In order to minimize the error between the anticipated welding route and the actual welding path, My et al [18] developed an inverse kinematic algorithm for welding robots that worked with a rotating translator. The problem of welding path planning in practical engineering usually includes welding sequence planning and welding spot path planning, for the mixed path planning problem, Zhao et al [19] proposed a hybrid path planning method based on the memetic algorithm for the Spot-Welding Robots in the processing of curved surface workpieces of body-in-white. In addition to the use of algorithms for path planning, innovation in path planning methods for different working conditions is also an effective means [20][21][22][23].…”