Stochastic optimization-based approach for multifingered grasps synthesis

Abstract

In this paper, we propose an approach for computing suboptimal grasps of polyhedral objects. Assuming n hard-finger contact with Coulomb friction model and based on central axes of the grasp wrench, we develop a new necessary and sufficient condition for n-finger grasps to achieve force-closure property. Accordingly, we reformulate the proposed force-closure test as a new linear programming problem, which we solve using an interior point method. Furthermore, we present an approach for finding appropriate stable grasps for a robotic hand on arbitrary objects. We use the simulated annealing technique for synthesizing suboptimal grasps of 3D objects. Through numerical simulations on arbitrary shaped objects, we show that the proposed approach is able to compute good grasps for multifingered hands within a reasonable computational time.

An Attentional Approach to Human–Robot Interactive Manipulation

“…As the choice of a grasp to grab an object greatly determines the success of the task, we developed a grasp planner module for interactive manipulation [38]. Even for simple tasks like pick and place or pick and give to a human, the choice of the grasp is constrained at least by the initial and final position accessibility and by the grasp stability [6]. The manipulation framework is able to select different grasps depending on the clutter level in the environment (see Figure 7).…”

Efficient models for grasp planning with a multi-fingered hand

“…The inputs to the test are the contact positions and normals. The test is based on a force-closure test, solved as a linear programming problem [29]. All the grasps that do not verify force-closure are discarded.…”