Automated Trajectory Planning and Analytical Improvement for Automated Repair by Robot-Guided Cold Spray

Abstract

Cold spraying has emerged as a promising technique for the repair of metallic components. Manipulating the cold spray gun by industrial robots, referred to as robot-guided cold spraying, enables flexible and controlled material deposition. This work proposes a concept for automated planning of robotic cold spray paths and trajectories, enabling effective and efficient material deposition at specified repair locations. The concept incorporates predefined cold spray parameterizations and boundary conditions to provide the best possible material deposition for the individual repair application. The concept begins with the extraction of the volume to be filled. This volume is then sliced into suitable adaptively curved layers and converted into point clouds for path planning. Subsequently, the cold spray path is converted into a trajectory by adding a calculated spray velocity profile to produce the required locally varying layer thicknesses. In addition, simulation of the material deposition and a kinematic analysis of the simulated trajectory are performed. These are utilized as performance indicators for assessing deposit quality and material efficiency, enabling the validation and improvement of the parameterized trajectory. Finally, the implementation of the entire concept is demonstrated by representative use cases. The results demonstrate successful automated path and trajectory planning by the proposed concept, contributing to the overall goal of automated repair of damaged components by cold spraying.