Simulation and experimental teaching design for robot deburring path planning: Taking deburring of wheel hub windows as an example

As the intelligent manufacturing sector expands its industrialization process, industrial robot technology continues to mature. Traditional teaching methods for this technology no longer suffice to adequately meet educational requirements. This paper aims to significantly enhance the practical robot operation skills of students majoring in intelligent manufacturing engineering and to enrich teaching content in industrial education by exploring simulation and experimental teaching design for robot deburring path planning.

First, we designed a deburring system for wheel hub windows that integrates industrial robot technology with machine vision. This system automates the positioning, recognition, and deburring path planning for wheel hub workpieces. Using Bezier curves, we designed the deburring path while considering robot kinematics and the 3D model of the wheel hub, optimizing the path length by accounting for the rotational freedom of the tool. By assessing the local curvature of the wheel hub window curve and its three-dimensional structure, adjustments are made to the tool position, contact point, and rotational and orientational angles to develop and execute an optimal tool angle strategy. The vision system is calibrated, deburring process parameters are configured, and the wheel hub workpiece is precisely configured. These allow the tool path to be adapted and the robot path to be crafted, resulting in comprehensive robotic deburring path planning. Subsequently, a robotic deburring experimental teaching approach was introduced, allowing teachers to clearly illustrate the fundamental principles and procedures of robotic deburring technology while offering personalized instructions and ongoing feedback based on student performance. Robot path planning simulation and actual robot deburring experiments were conducted using RobotStudio software for offline programming and simulation, and an experimental platform was established for conducting deburring experiments. The visual system gathered wheel hub pose information, enabling effective robot path planning and deburring operations.

The simulation results revealed that the robot maintained good contact with the wheel hub window edge, with the tool center point movement path being a smooth set of curves without obvious abrupt changes or bends. The joint angle change curve demonstrated no significant peaks, indicating smooth progression and gradual posture changes in the deburring tool. The experimental findings also demonstrated that the wheel hub edge was free of burrs or sharp edges postdeburring, and the chamfer size was within the 1.5 mm limit, demonstrating effective deburring quality and efficiency.

The proposed method provides an innovative experimental teaching case and implementation approach for experimental teaching in intelligent manufacturing engineering and industrial robot technology. It improves students’ practical skills in industrial robot deburring and offers a model for cultivating high-quality professionals in intelligent manufacturing.