In robotic grinding, significant tool deflection occurs due to the lower stiffness of the manipulator and tool, compared with operation by universal grinding machines. Tool deflection during robotic grinding operation causes geometrical errors in the workpiece cross section. Also, it makes difficult to control the grinding cutting depth. In this study, a method is proposed for calculation of the tool deflection in normal and tangential directions based on grinding force feedback in these directions. Based on calculated values, a real-time tool deflection compensation (TDC) algorithm is developed and implemented. Force interaction between the tool and workpiece is significant for grinding operation. Implementing grinding with constant normal force is a well-known approach for improving surface quality. Tool deflection in the robotic grinding causes orientation between the force sensor reference frame and tool reference frame. This means that the measured normal and tangential forces by the sensor are not actual normal and tangential interaction forces between the tool and workpiece. In order to eliminate this problem, a resultant grinding force control strategy is designed and implemented for a parallel hexapod-robotic light abrasive surface grinding operation. Due to the nonlinear nature of the grinding operation, a supervised fuzzy controller is designed where the reference input is identified by the developed grinding force model. This grinding model is optimized for the robotic grinding operation considering setup stiffness. Evaluation of the experimental results demonstrates significant improvement in grinding operation accuracy using the proposed resultant force control strategy in parallel with a real-time TDC algorithm.