The goal of this study was to develop a transfemoral prosthesis that realizes a natural and smooth gait. To realize such prostheses, the smoothness or goodness of walking in the swing phase should be investigated. So far, many studies have investigated the human gait. However, the goodness of walking has not been clearly defined. Passive walking has drawn much attention because it includes the essence of the gait with higyly energy-efficient walking. The human gait is thought to effectively utilize the dynamics of the body for a smooth gait. Investigating the human gait should help in building smoothly walking robots and realizing prostheses that make it easy to walk. The present paper proposes a method to evaluate the inertial motion of the human gait in the swing phase and a method to generate the joint motion profile of a transfemoral prosthesis that utilizes its inertial motion. First, an inertial motion index is proposed to evaluate the closeness of the given motion to the inertial motion of multilink systems. The gait of healthy participants in the swing phase was analyzed using the proposed index. The results showed that inertial motion is effectively used in the middle of the swing phase. Based on the results, a motion generation method is proposed for the knee joint of a prosthesis that utilizes the inertial motion in the middle of the swing phase. Simulation results with the method showed that a smoother change in torque was realized compared to another method that uses the measured joint motion of human gait as the desired trajectory for the PD controller.

The basis-motion torque composition (BMC), which generates feedforward torque for precise joint-trajectory tracking of a multi-joint robot arm, has been recently suggested. It is based on four arithmetical operations of time-series torque data of several motions preliminarily obtained by the iterative learning control. The remarkable advantage of BMC is to generate desired feedforward torque without prior information of dynamics parameters. However, the class of torque generated by the BMC has been restricted. The paper presents an enhanced BMC which permits generation of motions with different motion-velocity profiles among joints of a multi-joint robot. The algorithm is presented and the validity of algorithm is confirmed through numerical simulations in the case of a two-joint robot arm under the influence of gravity. Furthermore, a class of applicable systems of BMC approach is discussed.

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.

This paper focuses on generation of feedforward torque for precise joint-trajectory tracking of a multi-joint robot arm with serially connected links. A proposed method called basis-motion torque composition, based on four arithmetical operations of time-series torque data for several motions, allows to generate feedforward torque for a motion whose final posture and time profile are specified. The torque-generation algorithm is presented, and the experimental results by a two-joint robot arm are illustrated. The experimental results demonstrate that the tracking errors of angular velocities by the basis-motion torque composition tend to be smaller than those by the computed torque method.

This paper focuses on the Riemannian distance and its application to skilled-motion plannings for the system. The Riemannian distance from one pose to another and vice versa is defined as the minimum curve-length measured by the Riemannian metric based upon the system inertia matrix among all curves connecting the two poses. The minimum-length curve in this meaning is called “geodesic” and reflects a movement of the system affected only by inertia-tensor-originated force (i.e., pure inertia, centrifugal, and Coriolis forces). In order to investigate in detail such a movement along the geodesic, some computer simulations are conducted in the cases of planar motions by a 4-DOF robot arm and biped walkings by a wholebody robot. It is shown through simulation results that movements attaining the Riemannian distance (natural movements in inertial actions) in the two cases tend to be similar to those in human skilled motions when human-scale robot models are chosen. Based upon the Riemannian distance, motion plannings for multi-body systems using physical properties inherent in their own physical structures are discussed.

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 proposes an iterative learning control (ILC) scheme for a class of redundant robot arms to acquire the desired control input signals that produce an endpoint trajectory specified in task space. The learning update law of control input signals is constructed only in task space by modifying the previous control input through adding linearly an endpoint velocity trajectory error. Although the dimension of the task space is strictly less than the DOF (degrees-of-freedom) of the robot arm, the proposed method need neither consider any inverse kinematics problem nor introduce any cost function to be optimized and to determine the inverse kinematics (or dynamics) uniquely. Convergence of trajectory trackings to the specified one is shown by numerical simulations in both cases 1) free-endpoint motion and 2) constraint-endpoint motion with specified contact force. A theoretical proof of convergences in the case of free-endpoint motion is given on the basis of an approximated dynamics linearized around a desired solution in joint state space.

A natural control method for resolving the ill-posedness of inverse kinematics of multi-joint reaching movements under redundancy of degrees-of-freedom (DOF) is proposed, which need neither introduce any artificial performance index to determine the inverse kinematics uniquely nor calculate the pseudo-inverse of the Jacobian of task coordinates with respect to joint coordinates. The control signal is composed of a linear superposition of three terms 1) damping shaping, 2) task-space position-error feedback with a single stiffness parameter, and 3) gravity compensation by means of estimation of uncertainty in the potential energy. It is shown through computer simulation and theoretical analysis that the signal can generate smooth reaching motions provided that a set of damping factors and the stiffness parameter are selected in a synergistic way. A physical meaning of each term of the control signal is discussed from the viewpoints of Newtonian mechanics and neuro-physiology. It can be concluded from those illustrative examples that mechanical robots with redundant DOFs can be endowed by synergistic adjustments of damping factors and a stiffness parameter with ability of generating human-like skilled motions

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

Object manipulation involves two tasks: 1) reaching to grasp and 2) grasping. Motivated by physiological studies related to first task, reaching to grasp, and a simple control method composed of joint-damping and a single virtual spring, we try out for realization of continuous reaching-to-preshaping movements by robotic hand-arm systems with a pair of 2DOFs fingers and a 3DOFs arm. Differently from conventional researches, this paper treats neither trajectories planning nor inverse kinematics. Instead of those, a few transit point and desired point in task-space and a control method with Jacobian transpose and joint velocity damping are merely adopted. Based on results of numerical computer simulation, it is concluded that it is possible to simply realize continuous robotic reaching-to-preshaping motion by adopting the transit points and the control method

A simple control method for redundant multi-joint arm was proposed recently by gaining a physical insight into human multi-joint reaching movements in redundancy of DOFs. Differently from the traditional approaches, the method need neither introduce any artificial performance index to resolve kinematics ill-posedness nor calculate the pseudo-inverse of the Jacobian matrix of task coordinates with respect to joint coordinates. This novel approach is based upon an idea of "virtual spring-damper hypothesis," and the control signal is composed of linear superposition of three terms 1) joint-damping, and 2) virtual damper effects in parallel to 3) virtual spring effects in task space. This paper shows through experiments by using an industrial robot arm (PA-10) with redundant multi-joints that the control signal can generate smooth reaching motions without incurring any annoying self-motion even in the case of industrial robots. It is shown further that virtual damping effects in task space play an important rule in making endpoint trajectories of the robot arm quasi-straight. Consequently, the control signal can easily generate human-like multi-joint movements of robot arms without spending a huge amount of computational cost for motion plannings of not only the endpoint trajectory but also each joint trajectory

This paper explores what are the fundamentals of physiologically inspired robot control through investigating two interesting but difficult problems of robot control: 1) robotic hand-writing and 2) human-like multi-joints reaching with surplus DOFs (Degrees-of-Freedom). Noteworthy characteristics in control of these systems are a) redundancy in DOF, b) dexterity in execution of a target task, and c) indispensability of sensory motor coordination, though d) their dynamics are nonlinear and governed by geometric constraints in the former system. Due to these inherent characteristics, both the conventional control-theoretic approaches originated from the linear system theory and Lyapunov’s direct method are likely to fail. By gaining physical insights into these nonlinear dynamics with redundancy in DOFs and physical descriptions of target tasks, this article claims that a symbiosis of “robotics” and “neuro-physiology” is quite effective in finding a simpler sensory-motor coordination principle in each case that leads to accomplishment of each imposed task regardless of annoying characteristics of its motion dynamics with nonlinearity and DOF-redundancy.

A simple control method for 3-dimensional multi-joint reaching movements under redundancy of Degrees-of-Freedom is proposed, which neither need to introduce any performance index to solve inverse kinematics uniquely nor need to calculate pseudo-inverse of the Jacobian matrix of task coordinates with respect to joint coordinates. The proposed control signal is composed of linear superposition of three terms: 1) angular-velocity feedback for damping shaping; 2) task-space position feedback with a single stiffness parameter; and 3) compensation for gravity force on the basis of estimates for uncertain parameters of the potential energy. Through a variety of computer simulations by using a whole arm model with five DOFs, the importance of synergistic adjustments of damping factors as well as its relation to selection of the stiffness parameter is pointed out. It is shown that if damping factors are chosen synergistically corresponding to the inertia matrix at the initial time and the stiffness parameter then the endpoint converges asymptotically to the target position and reaches it smoothly without incurring any self-motion.