Object Manipulation using Robotic Hands with Varying Degrees of Grasp Knowledge

In this paper, we propose a robust control framework for object manipulation for when the robotic hand has limited knowledge of the grasp scenario. The framework considers a hand-object system subject to disturbances resulting from uncertainties in the object center of mass/inertia, hand kinematics, external wrenches, and contact locations. The framework guarantees semi-global asymptotic stability and exponential stability of the uncertain hand-object system with respect to object manipulation. The proposed framework is then applied to practical object manipulation scenarios with different levels of uncertainty related to the sensors available to the robotic hand. These scenarios include when the hand-object system is known perfectly; when vision sensors are available; when tactile sensors are available; and when no vision/tactile sensors are available to the robotic hand (i.e. blind grasping). The analysis also addresses the internal force control in relation to the various practical cases. Simulation and experimental results validate the effectiveness of the proposed approach.