Open AccessApplication of sequential quadratic programming for obtaining optimal obstacle avoidance posture and end position of a 7-axis robotic manipulator
Author(s) -
Tuo Huang,
W J Chen
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1113/1/012002
Subject(s) - sequential quadratic programming , control theory (sociology) , obstacle avoidance , quadratic programming , position (finance) , obstacle , computer science , computation , software , matlab , control engineering , mathematical optimization , mathematics , robot , artificial intelligence , engineering , algorithm , control (management) , programming language , finance , mobile robot , political science , law , economics , operating system
This paper used sequential quadratic programming (SQP) method to obtain the optimal obstacle avoidance posture and end position of a 7-axis robotic manipulator. By applying restraining conditions, obstacle information, and finishing point coordinates, a homogeneous transformation matrix was firstly used to construct a space for limited movement for the first and sixth axes of the robotic manipulator. Subsequently, we determined whether the terminal point was within reach of the robotic manipulator and calculated the angle of each axis. Finally, the MATLAB software was used to conduct a simulation and verification. In this study, the SQP method was used to introduce inequality constraints into the computation and conducted the iterative method. The simulation results revealed that the method can obtain avoidance of obstacle postures and select optimal values from the iteration results of multiple initial values to avoid the local optimal problem. Overall, the research findings are that the functions and applicability of the 7-axis robotic manipulator can be extended in industry when applied in future intelligent manufacturing.