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Grasping in robot gripper is an operation that is inevitably performed by prosthetic hands or industrial robots. Meanwhile, slipping of the grasped object is considered as an undesirable phenomenon in any kind of grasping. Here, the computed torque control is used in order to slip control and also guarantee the desired behavior of the closed loop system. Nevertheless, any acceleration changes of the robot’s joints before completing the response time of the slip controller, influence directly on the object position relative to the robot and causes slip phenomenon. However, the applied computed torque controller is proper for tracking trajectory but this desired trajectory will be altered according to slip occurrence. This paper introduces a method to modify the desired trajectory during grasping an object. The modification is done according to the measured slip. These methods not only control the slip of the grasped object, but also compensate it. So the object could be handled and placed in its proper position in the task space. This approach guarantees the safe grasping and moving objects according to object position relative to the gripper.

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This paper deals with the problem of safe grasping of an object. According to robot maneuvers during of movement, the slipping or falling of the objects is possible. Here, an adaptive backstepping control method is used for controlling of slipping and tracking of desirable paths. First, the robot dynamics of grasping of an object including mechanical arm with three rotational joints, one prismatic joint, jaw gripper as well as dynamic of the electrical actuators is derived. Then, backstepping technique, which is a systematic approach based on Lyaponov theory, is applied for this nonlinear system. Beacuse of existence of different uncertainties in this system such as mass and inertia of robot and object mass, it is required to design a controller to be able to cope with these uncertainties. Accordingly, a stable controller using adaptive backstepping control methodology is also designed to estimate of these parameters’ uncertainties. Stability analysis is provided based on Lyapunov theory. Simulations are carried out to evaluate the performance of the proposed controller. Results show the effectiveness of the proposed control method.