工业机器人距离误差空间相似性建模与补偿OA

Industrial robots have become important carriers for automated assembly due to their high flexi-bility.However,in assembly tasks that have strict requirements for the distance between critical points on the dimensional chain(such as peg-in-hole assembly),the existing absolute positioning accuracy of robots often struggles to meet the requirements.Currently,the main methods for improving industrial robot accu-racy include kinematic calibration and spatial interpolation.However,kinematic calibration often pursues optimal global accuracy and fails to sufficiently consider the high-precision requirements of local discrete points on critical assembly paths;spatial interpolation is prone to introducing cumulative errors during the coordinate system transformation process,making it difficult to achieve the required assembly precision.To this end,this paper proposed a distance error prediction model and compensation method to improve the accuracy of critical points of robots in assembly tasks.First,the kinematic model of the robot was es-tablished,its position error model was derived,and an error model with distance error as a constraint was constructed to avoid error accumulation caused by coordinate system transformation.Second,by establish-ing the error mapping relationship between joint space and task space,the similarity characteristics of dis-tance error in space were quantitatively revealed,and the variogram was used to quantitatively describe this similarity,providing a theoretical basis for interpolation point planning.Then,a distance error interpo-lation prediction model was constructed in the task space,and a transformation method from scalar error to vector error was proposed to realize the synchronous correction of error magnitude and direction.Finally,accuracy tests and assembly application experiments were conducted on a standard 6-DOF industrial ro-bot.The experimental results demonstrate that after applying the proposed compensation method,the maximum and average positioning errors of the robot are reduced to 0.10 mm and 0.04 mm,respectively.Compared with kinematic calibration and the inverse distance weighting(IDW)method,the positioning errors are reduced by 66.77%and 49.51%,respectively.Furthermore,the assembly application experi-ments indicate that the maximum and average assembly positioning errors decrease from1.16 mm and 1.11mm(before compensation)to 0.15 mm and 0.05 mm,respectively.These results verify the effec-tiveness of the proposed method in assembly applications,providing a novel compensation strategy for the high-precision operation of industrial robots.