Abstract
Robot-guided cold spraying is currently developing as a technique with great potential for the repair of metallic components, particularly for depositing heat- and oxidation-sensitive materials. In this regard, the use of automation and robotics enables flexible control of the repair process. To ensure an optimal repair process, it is essential to consider the various requirements of robot-guided cold spraying already during the simulative planning phase. However, conventional robotic repair trajectories often do not fully consider the geometric constraints of material deposition, efficient material use, and the underlying limitations of robot kinematics. This work proposes the application of trajectory optimization by mathematical optimization for repair by robot-guided cold spraying. In this context, the optimal repair strategy must handle the constant material flow by the spray jet, which inevitably couples local material deposition with the robot motion. For this purpose, decision variables, objective function, constraints and a material deposition model are formulated to control the amount of deposited material accordingly. The goal is to generate an optimized trajectory that incorporates the requirements of cold spraying and robot kinematics to guarantee high-quality repair and efficient material use. This includes minimizing excess material and minimizing the jerk of the robot motion. The results demonstrate successful application of the trajectory optimization for component repair by cold spraying.
