Lei, M, Zhang, X, Yang, W and Zhang, G (2025) Inverse kinematics solution method based on workspace analysis and iterative step coefficient adjustment of general robot. Measurement. ISSN 0263-2241

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Abstract

General robots do not meet the Pieper criterion and require swift, precise inverse kinematics solutions for accurate control. Current numerical techniques lack universal applicability and desired convergence. This study proposes a numerical iterative method that combines workspace analysis with iterative step coefficient adjustment. An error function is constructed, and the manipulator’s workspace is delineated using Monte Carlo random sampling. The spatial point with the minimum error function is identified, and its joint variables are used as optimal initial inputs. An iterative step coefficient, adjusting in real time based on adjacent iteration steps, ensures rapid convergence within a predefined error threshold. Experimental validation of the proposed method was performed on the manipulator of the anchor drilling robot. The average angle errors along the X, Y, and Z axes were 2.1147°, 2.1426°, and 1.1800°, respectively, while the position errors were approximately 0.001 mm. In comparison with the conventional method, the angle errors were significantly reduced by 61.27 %, 50.91 %, and 45.65 %, respectively. Additionally, the computation time and the average number of iterations were decreased by 17.99 % and 20.01 %, respectively. Experimental results demonstrate its effectiveness for general robots with different structures, marking a significant advancement in motion control technologies for manipulators.

Item Type:	Article
Uncontrolled Keywords:	0102 Applied Mathematics; 0801 Artificial Intelligence and Image Processing; 0913 Mechanical Engineering; Electrical & Electronic Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering
Publisher:	Elsevier
SWORD Depositor:	A Symplectic
Date Deposited:	21 Jan 2025 15:03
Last Modified:	21 Jan 2025 15:15
DOI or ID number:	10.1016/j.measurement.2025.116807
URI:	https://researchonline.ljmu.ac.uk/id/eprint/25353

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