In this paper, a new algorithm for online grasping force optimization (GFO) of a dextrous robotic hand is presented. The GFO problem is cast in a convex optimization problem, considering also torque joint constraints. The proposed formulation allows to simplify the computational complexity of the problem by dynamically reducing the number of active torque constraints. Moreover, differently from other approaches, it does not require the evaluation of a new initial point at the beginning of each iteration. The effectiveness and the performance of the proposed method have been tested in a simulation case study where the hand manipulates a load with time-varying mass.
Online dextrous-hand grasping force optimization with dynamic torque constraints selection / Lippiello, Vincenzo; Siciliano, Bruno; Villani, Luigi. - (2011), pp. 2831-2836. (Intervento presentato al convegno IEEE International Conference on Robotics and Automation tenutosi a Shanghai, PRC nel May) [10.1109/ICRA.2011.5979674].
Online dextrous-hand grasping force optimization with dynamic torque constraints selection
LIPPIELLO, VINCENZO;SICILIANO, BRUNO;VILLANI, LUIGI
2011
Abstract
In this paper, a new algorithm for online grasping force optimization (GFO) of a dextrous robotic hand is presented. The GFO problem is cast in a convex optimization problem, considering also torque joint constraints. The proposed formulation allows to simplify the computational complexity of the problem by dynamically reducing the number of active torque constraints. Moreover, differently from other approaches, it does not require the evaluation of a new initial point at the beginning of each iteration. The effectiveness and the performance of the proposed method have been tested in a simulation case study where the hand manipulates a load with time-varying mass.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
