The problem of object manipulation with no prior knowledge of object pose and geometry constitutes a key problem in the domain of service robotics. The grasping methodologies reported so far use either force closure or friction between the fingers and the object surfaces. Force closure leads to stable grasping such that the total sum of forces acting upon the object becomes zero [1]. Grasping methods based upon friction are better suited for grippers with limited degrees of freedom, for which force closure is infeasible due to gripper geometry. The fundamental objective is to maximize the contact area and thereby the friction force between the gripper and the object by selecting suitable contact points. In order to determine optimal contact points, [2] and [3] proposed vision based grasp point selection from the extracted contours of the object. Subsequently, the force applied to the object is determined based upon the selected grasp point and object properties. The force required for stable grasping is difficult to predict due to the presence of friction in gripper actuators as well as the nonlinear behavior of gripper and object materials. Conventional control strategies are not suitable for such conditions. Therefore [4] investigates a fuzzy logic approach for force control. Reference [5] addresses this issue from a different perspective as slippage is detected by means of dynamic tactile sensing.