Three-fingered Robot Hand Research Articles

Dynamic grasp planning of multifingered robot hands based on asymptotic stability

We describe an approach for planning grasps of multifingered robot hands based on a small vibration model. Using features of the grasp configuration, we analyze asymptotic stability, contact situations, and uniaxial fingertip force constraints for the combined planning of finger posture and finger position, and characterize the generalized mass, damping, and stiffness. Choosing the largest time constant of the vibration model as an optimization criterion for planning finger postures and positions, the original problem of dynamic grasp planning is formulated as a nonlinear program. Simulation examples for a three-fingered robot hand grasping a spherical object demonstrate the effectiveness of the approach.

３指ハンドを用いた操りにおける指の滑りと対象物運動の制御

Dynamic control of a three-fingered robot hand manipulating an object in three-dimensional space while allowing one of the three fingers to slide so that to change its grasp location on the object surface is formulated. The static and dynamic friction at the grasp point of the sliding finger on the object surface is considered explicitly and their effects to the finger and object behaviors are discussed. Motion equations of the whole system are derived and a dynamic control law for realizing the desired object motion as well as the desired finger sliding and the desired grasping force is proposed. The realizability of the given trajectories under the constraints of maximal static friction and dynamic friction at the grasp points, and of joint driving torque, are also discussed. A simulation example to demonstrate the use of the proposed control law is given. The results of this work will be useful for a multifingered robot hand in certain tasks to perform regrasping and reorientation of an object without breaking the grasping.

Development of a three-fingered robot hand with stiffness control capability

The development of a three-fingered robot hand with stiffness control capability is reported. The hand consists of three fingers each of which includes three joints. Each joint is actuated through a tendon-sheath transmission by a D.C. servo motor separately situated from the hand. A potentiometer and a newly-developed tension differential-type torque (TDT) sensor is installed at each joint. To control the joint stiffness by software, a stiffness control algorithm is executed on the computer, and the joint actuators are conjointly controlled using the joint position and torque information. The mechanisms and control of the hand system are described and the stiffness control capability of the developed hand is experimentally confirmed. Furthermore, the position-stiffness based manipulation control method previously proposed is successfully implemented in the hand.

Grasp Synthesis of Polygonal Objects Using a Three-Fingered Robot Hand

Grasping an object with a multifingered robot hand requires complete constraint of its motion by contacts. Complete con straint of an object can also be described using force equilib rium. If any external force on the object can be balanced by applicable contact forces, a stable grasp has been achieved. A force closure grasp is such a grasp. This article presents a simple and efficient algorithm to find an optimum force clo sure grasp of a planar polygon using a three fingered robot hand. The optimum grasp is defined as a grasp that has the minimum value of a heuristic function. The heuristic function is formulated from the consideration of the possible uncertainties inherent in implementation. Even though a planar force clo sure grasp can be obtained using only two friction contacts, we consider only grasps where all three friction contacts explicitly participate. To find the optimum grasp, all feasible combina tions of edges and/or vertices are identified first. An edges and/or vertices combination is feasible when a stable grasp is attainable by an appropriate selection of three contacts on them. Then, using computational geometry, a single grasp is constructed on each feasible combination. Finally, the grasps obtained are compared using the heuristic quality measure. A test of our algorithm on several different polygons shows that the resulting grasp is realistic and is obtained fast enough for real-time use.

３本指ハンドによる対象物の操りにおける滑り運動の解析

In this paper, a quasi-static object manipulation by an articulated three-fingered robot hand with slip motion of grasping is discussed. This kind of manipulation achieves more dexterous manipulation by robot hands. The equilibrium relations of fingertip forces for grasping an object are solved in three dimensions. It is assumed that a slip happens when the fingertip forces go beyond the bound of the cone of maximum static friction. Possible directions of slip within a grasp are determined from the analysis. The fingertip force which achieves a desired slip motion is determined uniquely. Finally the set of fingertip forces is obtained, and the planning method of slip motion is dicussed.

Efficient fingertip force computation for object manipulation using dexterous robot hand

Multifingered hands, or parallel manipulators, can be used to grasp and manipulate objects. Effective finger force computation is necessary for successful manipulation of an object by a multifingered robot hand. This paper presents an efficient computational procedure to obtain finger force of a three-fingered robot hand in object manipulation. We first define initial grasping force as the force to hold a massless object. Then grasping force and contact normal during manipulation are determined from initial grasping force and initial contact normal by tracking the object displacement. Manipulation force, the finger force required to manipulate an object and to compensate for object weight, is computed by the generalized matrix inverse method. Optimal internal force, when necessary, is determined from the grasping force during manipulation without explicitly solving the optimization problem. The computational burden to determine finger force in this paper is less than previous methods.