Robotic grinding surface topography modeling considering motion trajectories and accurate shapes of abrasive grains

Surface morphology is critically important in material processing. Existing studies on surface morphology modeling mainly focused on constant abrasive grain shape, which can partially reflect the actual shapes of abrasive grains and provide preliminary surface predictions. However, the overlook of grain shape variations and the influence of motion trajectories restricts accurate surface morphology predictions, and the further hinders the enhancement of surface quality. This paper introduces a novel approach to address these gaps. First, a model is established to determine the effective number of abrasive grains based on their distribution, enabling calculation of the maximum penetration depth under a given grinding force. The shapes of the abrasive grains, accounting for variations and irregularities, are modeled as ellipsoids with varying geometric parameters. Following this, the motion trajectories of both single and multiple abrasive grains are modeled through kinematic calculations, enabling accurate prediction of the workpiece surface topography and providing a theoretical foundation for optimizing surface quality. Experiments conducted on a robotic grinding system equipped with a pneumatic force-controlled actuator demonstrate that surface topography can be accurately predicted and significantly improved. The proposed surface topography modeling method, which accounts for the shape variations and motion trajectories of abrasive grains, achieves higher prediction accuracy and better surface quality compared with existing studies.