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This paper introduces a novel approach to address the problem of PhysicalRobot Interaction (PRI) during robot pushing tasks. The approach uses adata-driven forward model based on tactile predictions to inform the controllerabout potential future movements of the object being pushed, such as astrawberry stem, using a robot tactile finger. The model is integrated into aDeep Functional Predictive Control (d-FPC) system to control the displacementof the stem on the tactile finger during pushes. Pushing an object with a robotfinger along a desired trajectory in 3D is a highly nonlinear and complexphysical robot interaction, especially when the object is not stably grasped.The proposed approach controls the stem movements on the tactile finger in aprediction horizon. The effectiveness of the proposed FPC is demonstrated in aseries of tests involving a real robot pushing a strawberry in a cluster. Theresults indicate that the d-FPC controller can successfully control PRI inrobotic manipulation tasks beyond the handling of strawberries. The proposedapproach offers a promising direction for addressing the challenging PRIproblem in robotic manipulation tasks. Future work will explore thegeneralisation of the approach to other objects and tasks.

Deep Functional Predictive Control for Strawberry Cluster Manipulation using Tactile Prediction