Abstract-This paper presents an algorithm to compute precision grasps for bulky objects using two anthropomorphic hands. We use objects modeled as point clouds obtained from a sensor camera or from a CAD model. We then process the point clouds dividing them into two set of slices where we look for sets of triplets of points. Each triplet must accomplish some physical conditions based on the structure of the hands. Then, the triplets of points from each set of slices are evaluated to find a combination that satisfies the force closure condition (FC). Once one valid couple of triplets have been found the inverse kinematics of the system is computed in order to know if the corresponding points are reachable by the hands, if so, motion planning and a collision check are performed to asses if the final grasp configuration of the system is suitable. The paper includes some application examples of the proposed approach.

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This paper presents a method to compute con-\ud tact forces for bimanual grasps. The method is based on the\ud optimization of the force distribution of the hands and min-\ud imizing the force exerted by each finger, using two different\ud cost functions. Both cost functions and the constrains of the\ud optimization problem are formulated as functions of the joint\ud torques based on the existing relation between the grasping\ud forces, the hand-jacobian matrix and the torque of the joint\ud fingers. Additionally, a bimanual grasp index is presented to\ud measure the force distribution between the hands. The paper\ud includes some application examples of the proposed approacPeer ReviewedPostprint (author's final draft

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This paper presents a framework schema that allows to bring simulation results obtained from different dual-arm robotic applications to executions in real environments. The framework uses the Robot Operating System\ud (ROS) to communicate each component of the dual-arm, and the robotic software tool The Kautham Project for the computation of motion paths, inverse kinematics validations, collision checking and the graphical visualization of the simulated environment. The Anthropomorphic Dual Arm Robotic System (ADARS) was used in this work which is composed of two robotic arms of 6 degree of freedom, two anthropomorphic hands, and tactile sensors in the fingertips. The real execution of two different applications are presented to show the robustness of the framework. The\ud resulting framework is general enough, allowing the reimplementation with minimum changes in any other dual-arm system.Postprint (published version