This paper analyzes grasp stability of two objects in two dimensions. In the previous researches on the grasp stability, the number of grasped objects is restricted to 1. For efficiency of tasks, multiple objects had better been grasped and manipulated by a robot hand. In order to design stable grasp, grasp stability of multiple objects must be quantitatively evaluated. In case of two grasped objects in two dimensions, the number of parameters of object displacement is 6. However, the displacement of the objects is constrained by each other, because the contact between the objects must be maintained. Independent parameters of the object displacement are provided and then finger displacement is derived. The grasp stability is evaluated from the viewpoint of the potential energy method. From numerical examples, the effect of curvature at contact point between two objects is demonstrated. The effect of this curvature stands for the feature of multiple objects.

This paper proposes an algorithm for identification of contact conditions between a grasped object and external environment from position and velocity information of a robot hand. The contact conditions mean contact type, contact position, and contact force. Soft finger contact type, line contact type, and plane contact type are considered in addition to point contact type. The contact type is identified by rank of the matrix that places estimated angular velocity of the object at contact point. Contact position, contact normal and contact line are also estimated. This method has the following merits as compared with the method using 6-axes force information described in the previous paper. The identification problem is reduced to the problem of solving linear equations. The required number of active sensing motion is less.

This paper discusses a method for identification of contact conditions from the information of 6-axes force sensor equipped with a robot hand. The previous paper (1999) has the following problems: the noise of sensing force was not considered, and hence the estimates obtained by the previous method are biased from true value, and the identification of contact types depends on an unknown contact position. In this paper we consider the noise of force. We propose a method of removing the bias from the estimates. Hence, it is guaranteed that asymptotically unbiased estimates are obtained. The contact types can be judged by eigenvalues of a covariance matrix, which is derived from estimates of the contact moment. The effectiveness of the algorithm is demonstrated by simulations.

We discuss stability of 3D grasps by using a three-dimensional spring model (3D spring model). Many works have described stability of a frictionless grasp. These works used a one-dimensional spring model (1D spring model) for representation of frictionless contact as a matter of course. However, a 1D spring model involves the following problems: (i) displacement of a finger is restricted to one dimension along the initial normal at contact point; and (ii) it is not clearly considered that a finger generates contact force to the object along the normal direction only. To overcome the problems and provide accurate grasp stability, we introduce a 3D spring model. Then a finger's displacement is relaxed and a finger's contact force is precisely formulated. We analyze grasp stability from the viewpoint of the potential energy method. From numerical examples, we show that there exists an optimum contact force for stable grasp. Moreover, we also analyze a frictional grasp by using contact kinematics of pure rolling. By comparing frictional grasp stability with a frictionless one, we prove that friction enhances stability of a grasp.

When a grasped object is in contact with external environment, it is required to identify contact conditions prior to performing the assembly tasks. This paper discusses a method for identification of contact conditions from the information of force sensor equipped with the robot hand. This paper treats the practical case where sensing data are contaminated with noise. We propose an efficient and analytical algorithm for identifying contact conditions by using an active force sensing method. The algorithm can identify not only contact position and contact force, but also contact type such as soft finger contact type, line contact type, and plane contact type. These contact types are characterized by a standard deviation of contact moments. The contact position is estimated by a least-squares method. The contact moment is then estimated from noisy observations and its eigenvalues are analyzed. The contact type can be judged by the eigenvalues of estimated contact moment. The effectiveness of the algorithm is demonstrated by simulations.

Proposes a method for analyzing the stability of grasps. The characteristic points in this paper are to consider the curvature of both hand and object at contact points and the grasp with friction and frictionless contact. From this analysis, it is shown that the grasp using round fingers is more stable than using sharp fingers. Moreover, we establish the condition on the finger's stiffness to stabilize the grasp with friction. It is proved that the required stiffness of fingers are decreased by considering the curvature. The stability analysis is greatly simplified by using potential energy of the grasp system and is of practical use.

A 6 DOF motion system using a new parallel link mechanism is developed for purposes of evaluating human motion sensation. This motion system is made up of three five-bar mechanisms, each of which has 2 degrees of freedom (DOF) and is driven by AC servo motors. Therefore, this system is very small and low cost, but its motion area is larger and its response is better than previous hydraulic Stewart platform. Furthermore, we have developed a high-speed parallel signal-processing controller for motion control and a new 6 DOF acceleration sensing system based on the parallel sensing concept. Combining the new motion and sensory system with multivideo system, we have built up a new analytical system for evaluating wide band-width of motion sensation in getting on such vehicles as automobile or airplane.

When assembly tasks are accomplished by robot manipulators, it is necessary to identify interactions between grasped objects and external environments, such as contact positions and contact type, and also contact directions. This paper discusses the identification of unknown parameters such as mentioned above. Point contact, line contact and plane contact are formulated in contact conditions. Applying this formulation, a simple scheme is proposed for identification of contact conditions by using active force sensing method. In this algorithm, contact type, contact direction and contact point can be identified.>