Grasping and Control of Multi-Fingered Hands

An important issue in controlling a multi-fingered robotic hand grasping an object is the evaluation of the minimal contact forces able to guarantee the stability of the grasp and its feasibility. This problem can be solved online if suitable sensing information is available. In detail, using finger tactile information and contact force measurements, an efficient algorithm is developed to compute the optimal contact forces, assuming that, during the execution of a manipulation task, both the position of the contact points on the object and the wrench to be balanced by the contact forces may change with time. Since manipulation systems can be redundant also if the single fingers are not -due to the presence of the additional degrees of freedom (DOFs) provided by the contact variables- suitable control strategies taking advantage of such redundancy are adopted, both for single and dual-hand manipulation tasks. Another goal pursued in DEXMART is the development of a human-like grasping approach inspired to neuroscience studies. In order to simplify the synthesis of a grasp, a configuration subspace based on few predominant postural synergies of the robotic hand is computed. This approach is evaluated at kinematic level, showing that power and precise grasps can be performed using up to the third predominant synergy.