Design and Trajectory Optimization of a Large-Diameter Steel Pipe Grinding Robot

Abstract

The distribution of internal defects in large-diameter steel pipes can be complicated. Due to the harsh working environments involved, the manual grinding method for correcting such defects is inaccurate, inefficient, and risky. Therefore, in this study, we designed a new internal pipe grinding robot with five degrees of freedom. The grinding trajectory was optimized, and dynamic and kinematic models of the robot were established for the internal space of a pipe with a diameter between 800 and 1,200 mm. The feasibility of the robot was verified by simulation. A trajectory optimization method that focuses on the time, energy, and impact of the trajectory of the grinding robot is proposed. The method uses modified multiobjective particle swarm optimization (MMOPSO) in the robot’s trajectory planning module to obtain a Pareto solution set. The analytic hierarchy process is used with the minimum fuzzy entropy (AHP-MFE) method in the decision-making module to select the most appropriate trajectory according to the relevant working conditions. The experimental results validated the space accessibility and trajectory optimization performance. Compared with the original trajectory, operation time was shortened by 15.4%, energy consumption was reduced by 17.5%, and impact was reduced by 12.4%. The experimental error was less than 2.8%. The experimental results showed that the pipe grinding robot is safe and efficient.