In aging societies, there is a strong demand for robotics to tackle problems resulting from the aging population. Patient transfer, such as lifting and moving a bedridden patient from a bed to a wheelchair and back, is one of the most physically challenging tasks in nursing care. We have developed a prototype nursing-care assistant robot, RIBA, that can conduct patient transfer using human-type arms. The basic robot motion trajectories are created by interpolating several postures designated in advance. To accomplish more flexible and suitable motion, adjustment using sensor information is necessary, because the patient's posture and positions in contact with the robot may differ slightly in each trial. In this paper, we propose a motion adjustment method in patient lifting using tactile sensors mounted on the robot arms. The results of experiments using a lifesize dummy are also presented.

In aging societies, there is a strong demand for robotics to tackle problems resulting from the aging population. We have developed a prototype nursing-care assistant robot, RIBA, which was designed to come in direct contact with patients and conduct physically challenging tasks. RIBA interacts with its object, typically a human, through multiple and distributed contact regions on its arms and body. To obtain information on such whole-body contact, RIBA has tactile sensors on a wide area of its arms. The regions where hard contact with the manipulated person may occur have almost flat surfaces, leading to surface contact involving a finite area, in order to reduce contact pressure and not to cause the person's pain. When controlling the position and orientation of the person, the relative positions and orientations of the distributed contacting surfaces should be preserved as far as possible to maintain stable contact and not to graze the person's skin. Preserving the force and the pressure pattern of each contact region using tactile feedback is also important to provide stable and comfortable human-robot physical interaction. In this paper, we propose a whole-body contact manipulation method using tactile information to meet these requirements.

This paper proposes a novel object manipulation method to regulate the position and attitude of an object in the task space with dynamic stability by using a triple soft-fingered robotic hand system. In our previous works, a dynamic object grasping method without use of any external sensing, called “the Blind Grasping”, has been proposed. Although stable grasping in a dynamic sense has been realized by the method, a simultaneous object position and attitude control has not yet been treated, so far. In this paper, instead of using any information of the real object position and attitude, virtual data of object position and attitude are introduced by defining a virtual frame. By using the virtual information, a control signal to regulate the virtual object position and attitude without use of any external sensing is designed. The usefulness of our proposed control method even under the existence of nonholonomic rolling constraints is illustrated through a numerical simulation result.

A Riemannian-geometry approach for control and stabilization of dynamics of object manipulation under holonomic or non-holonomic (but Pfaffian) constraints is presented. First, position/force hybrid control of an endeffector of a multi-joint redundant (or nonredundant) robot under a nonholonomic constraint is reinterpreted in terms of ldquosubmersionrdquo in Riemannian geometry. A force control signal constructed in the image space spanned from the constraint gradient can be regarded as a lifting in the direction orthogonal to the kernel space. By means of the Riemannian distance on the constraint submanifold, stability on a manifold for a redundant system under holonomic constraints is discussed. Second, control and stabilization of dynamics of two-dimensional object grasping and manipulation by using a pair of multi-joint robot fingers are tackled, when a rigid object is given with arbitrary shape. Then, it is shown that rolling contact constraint induce the Euler equation of motion in an implicit function form, in which constraint forces appear as wrench vectors affecting on the object. The Riemannian metric can be introduced in a natural way on a constraint submanifold induced by rolling contacts. A control signal called ldquoblind graspingrdquo is defined and shown to be effective in stabilization of grasping without using the details of information of object shape and parameters or external sensing. The concept of stability of the closed-loop system under constraints is renewed in order to overcome the degrees-of-freedom redundancy problem. An extension of Dirichlet-Lagrange's stability theorem to a system of DOF-redundancy under constraints is presented by using a Morse-Lyapunov function.

A new robot hand dynamics model with rolling constraints and with a saddle joint at one finger is proposed, where two saddle-joint actuations are considered to be orderless. Spinning motion around the opposition axis connecting two center points of each finger-tip contact area with an object is faithfully treated, and a viscosity model for damping rotational motion of the object is proposed. A class of control signals without referring to object kinematics or using external sensing is proposed. Finally, numerical simulation results show the stability of motion of the overall closed-loop dynamics supplied with the proposed control input.

This paper proposes a stable object grasping method to realize dynamic force/torque equilibrium by using a triple robotic fingers system with soft and deformable hemispherical fingertips. In the authors' previous works, ¿Blind Grasping¿ control scheme, which realizes stable object grasping without use of any external sensing such as vision, force, or tactile sensing in the case of using a pair of robot fingers, has been proposed. This control methodology is based on a unique configuration of human hand, called ¿Fingers-Thumb Opposability¿. In this paper, a ternary finger in addition to a pair of fingers is introduced not only to expand a stable region of grasping, but also to enhance dexterity and versatility of the multi-fingered robotic hand system. To this end, a ¿Blind Grasping¿ manner is modified in order to install it in the triple fingers system. First, dynamics of the triple robotic fingers system and a grasped object with considering rolling constraints is modeled, and a control input based on the blind grasping manner is designed. Next, the closed-loop dynamics is derived and a stability analysis is shown briefly. Finally, its usefulness is discussed through numerical simulation results.

Modeling of pinching an object with arbitrary shape by a pair of robot fingers with hemispherical ends in a horizontal plane is proposed in a mathematical and computational manner. Since the curvature of an object contour with an arbitrary curve is variable according to the change of the contact point between the object surface and the rigid finger tip, the arclength paremeter ¿s¿ explicitly appears in the overall fingers-object dynamics. It is shown that the overall fingers-object system should be accompanied with the first-order differential equation of the parameter ¿s¿ that includes the curvatures of both the object contour and finger-tip curve. A control input, which is of the same category as the control input called ¿blind grasping¿ appeared in our former papers, is utilized for the realization of stable grasp. The control input does neither need to use the kinematic information of the object nor use any external sensing. Finally, numerical simulations are carried out in order to confirm the effectiveness of our proposed model and control input.

This paper proposes an iterative learning control method for simultaneous force/position tracking tasks by using a 5 D.O.F. robotic thumb under non-holonomic rolling constraints. In our previous works, "blind touching", which is defined as a point-to-point control scheme for the robot to realize a desired contact position and a contact force simultaneously without any external sensing, have proposed. In this paper, an iterative learning control manner to realize a desired continuous trajectory of the center of the contact point together with a desired contact force on the task plane is proposed. The usefulness of this learning control method is demonstrated by showing results of computer simulations.

This paper shows through faithfully deriving Paffian forms of 3-D rolling contact constraints that 3-D pinching can be stabilized by using a pair of robot fingers with a hemispherical soft tip and minimum degrees of freedom under the gravity effect. The proposed control input is based on fingers-thumb opposition without using object information or external sensing. Stability analysis of the closed-loop dynamics is presented by using a Lyapunov method. Finally, for the sake of confirmation of effectiveness of the proposed control signals, numerical simulations are carried out.

This paper deals with dynamic object grasping and position control by using a triple-fingered robotic hand with hemispherical soft finger tips. In the authors’ previous works, a dynamic object grasping method by using a pair of robotic fingers, called “Blind Grasping”, which does not need to use any external sensing, was proposed. However, it is so far assumed that spinning motion around the opposite axis for the object does not occur during the overall movement, because there are only two opposite fingers and thereby the spinning is uncontrollable. By introducing a surplus finger in addition to a pair of robotic fingers, this spinning can be inhibited and it becomes controllable. In this paper, a triple-fingered robotic hand system with nonholonomic constraints is modeled, and a control input to realize stable grasping with object position control is proposed. Its usefulness and effectiveness are illustrated through some numerical simulation results.

Human can pinch or grasp and manipulate an object stably and dexterously. Accomplishment of such tasks is contributed from human hand's configuration, called "fingers-thumb opposability". This opposability of the thumb against other digits is specific and granted to only human among primates. When we use a cell phone, or change a TV's channel using a remote controller, we grasp it by a palm and digits other than the thumb, and push buttons using the thumb quickly, without looking the buttons. These kinds of thumb's movement seem to be one of the most intelligent movements in a human. Therefore, execution of such touching tasks without visual or tactile sensing is called in this paper "blind touching". The goal of this research is to realize humanlike "blind touching" by means of a 5 D.O.F. thumb robot model with soft and hemispherical finger-tip. To do this, we formulate a simultaneous contact position and touching force control by using 3-dimensional rolling contact with the task plane. First, dynamics of the 5 D.O.F. thumb robot model with hemispherical soft finger-tip under rolling constraints is derived. Then, a sensory-motor control law without vision, force or tactile sensing is proposed. Some numerical simulations show that the desired contact position and touching force can be attained by the proposed control scheme. A theoretical proof of convergence to the desired state is also presented.

This paper is concerned with construction of a mathematical model for a class of lumped-parameter dynamics of a pair of robot fingers with soft and deformable tips pinching a rigid object. It is then shown that, in the case of a pair of planer fingers with two and three joints and a 2D rigid object with parallel or non-parallel flat surfaces, there exists a sensory-motor coordinated control signal constructed by using only the knowledge of finger kinematics and measurements of finger joints such that it realizes secure grasping in a dynamic sense. This shows that a pair of robot fingers can grasp a thing securely in a blind manner. The result is further extended to the case of 3D object grasping and manipulation by a pair of soft fingers, one of which can move in 3D space.

A mathematical model expressing motion of a pair of multi-DOF robot fingers with hemi-spherical ends grasping a 3-D rigid object with parallel flat surfaces is derived together with non-holonomic constraints. By referring to the fact that human grasp an object in the form of precision prehension dynamically and stably by opposable forces between the thumb and another finger (index or middle finger), a simple control signal constructed from finger-thumb opposition is proposed and shown to realize stable grasping in a dynamic sense without using object information or external sensing (this is called "blind grasp" in this paper). Stability of grasping with force/torque balance under non-holonomic constraints is analyzed on the basis of the concept called "stability on a manifold". A few of preliminary simulation results is shown to verify the validity of theoretical results

This paper proposes a novel control method for enabling a robotic arm with a pair of two degrees of freedom (DOFs) robotic fingers as an endeffector to execute a variety of superimposed tasks in a coordinated way. Differently from conventional control methods previously proposed for arm-hand systems that adopt a separate design to control each robotic part, such as an arm and a hand, the proposed method designs a unified single control scheme for movements of the whole robotic arm-fingers system. It is assumed that finger-tips are rigid and there are rolling constraints between the finger-tips and a target object, and whole motion of the system is confined to the horizontal plane. The results of numerical computer simulation demonstrate that the proposed method is sufficiently effective in control of such a whole robotic arm-fingers system, and in particular is applicable to superimposed tasks, grasping, regulating, and replacing a target object through composition of the control signal based on the principal of superposition. It is concluded that special attentions in design of control signals should be paid to the wrist that combines the finger parts to the arm

Construction of a numerical simulator for 3-D object pinching and manipulation by a pair of robot fingers is described on the basis of mathematical modeling of physical interactions between the object and fingers under rolling constraints. The simulator consists of a set of Lagrange's equations of motion of the fingers and object under holonomic constrains and differential equations of nonholonomic constraints expressing rotational motion of the rigid object. By using this simulator, numerical simulation results of 3-D object pinching and manipulation under the gravity effect based on the control law rendering "blind grasping" without use of any object kinematics or any external sensing is carried out in a case that the fingers have excess joints. Numerical results show the validity of mathematical modeling and the control method

This paper is aiming at showing a sensory-motor coordination control scheme that realizes stable pinching of rigid objects with parallel or non-parallel flat surfaces movable in 2-dimensional vertical plane by a pair of robot fingers with hemispherical ends. The proposed control signal is composed of gravity compensation for fingers, damping shaping, exertion of forces to the object from opposite directions, generation of moments for rotational moment balancing, and regressors for estimating unknown steady-state terms, all of which neither need the knowledge of object parameters nor use any object sensing data. In other words, stable grasping can be realized by using only finger joint sensing in a blind manner without using force sensors and tactile sensing. Stability of pinching motion with convergence to the state of force/torque balance is shown through computer simulations and is also proved theoretically.

The human thumb is a digit playing crucial roles among all digits used for object manipulation. The special feature of the thumb termed as pad-opposition with four other fingers makes human precision manipulation possible, and during four other fingers dexterously manipulate an object, the thumb functions as a role of stably supporting other's manipulating motions within the pad-opposition. In various characteristics of the thumb, this paper concentrates upon the large radius of pad curvature of the thumb compared with those of four other fingers. In order to show the influence of the large pad curvature, it is shown that reiterated fingering motions can be easily generated by a pair of robotic fingers with different pad curvatures by using a sensory-feedback. It is also shown from computer simulations and experiments that the pad curvature automatically distinguishes roles of the thumb and other fingers. It is finally claimed that the thumb plays a crucial role in enhancement of dexterity and stability in such an implicit manner that it helps the other opposite finger with less pad curvature to make a swift rolling movement that can sophisticatedly control movements of the object.

This paper proposes a manipulation of a circular object in a horizontal plane by a pair of finger robots. This method guarantees the dynamic stability of the system and does not require any object models and object sensing to manipulate the object. It is assumed that there is no friction between the object and the horizontal plane and it is possible to be adequately large friction between the fingertips and the object. We examine the condition of stable grasping of a circular object and propose controllers for stable grasping and for controlling its approximate relative orientation angle without object sensing. The experimental results show the validity of the controller.

This paper proposes stable grasping and angle control methods of an object with parallel surfaces by a pair of finger robots in a horizontal plane. The method does not require any object sensing for stable grasping but only measurement of the object angle for absolute orientation angle control. Relative orientation angle control of the grasped object can be attained even if no object sensing is used.

This paper is aiming at clarifying the relationship between the total DOF (degree-of-freedom) of a pair of robot fingers and feasibility of concurrent control of stable grasping and object manipulation of a rigid object with non-parallel surfaces under the gravity effect. It is shown by computer simulation and an actual experiment that if each finger has at least two DOF then the desired task of concurrent stable grasping and posture control can be attained, though the use of a pair of dual fingers with three DOF is shown theoretically to be feasible. It is also shown that the use of fingers with single DOF and two DOF cannot be feasible under the gravity effect, though it is feasible in the case that the gravity effect can be ignored.