Estimation of joint torque is an important objective in the analyses of human motion. In particular, many applications seek to discern torque during a desired human motion, which is equivalent to solving the inverse dynamics. The computed torque method is a conventional means of calculating inverse dynamics. The obtained torque, however, invariably includes errors resulting from inexact inertial and viscoelastic parameters. This paper presents a method for solving the inverse dynamics of a human arm passively during tracking. To achieve precise human motion tracking, iterative learning control is used for motion generation. Some experiments that target a human arm are executed to validate the proposed method.

We have proposed the concept of Man-Machine Synergy Effectors. These are high-performance tools for human use, which are realized by introducing robot technology. It becomes possible to perform conventionally impossible tasks by human alone or robot alone, because the system synergizes better assets of both parties. In this paper, the concept of Man-Machine Synergy Effector is described. Then, the Power Pedal is introduced as a prototype of Man-Machine Synergy Effector for human lower extremities, which amplifies human leg power intuitively.

This paper proposes a tracking control method of sinusoidal motions utilizing stiffness adjustment of mechanical elastic elements for serial link systems. Although dynamics of the controlled objects is nonlinear, the stiffness adjustment realize a condition similar to a resonance of linear systems. We present a controller that adjusts stiffness of the elastic elements to reduce torque requirement of actuators while generating desired motions. The proposed controller works without using dynamics models nor parameters of the controlled objects. Stability of the controller is proved, and tracking errors are guaranteed to converge to a certain region. Simulation results demonstrate the validity of the proposed method. We also present an application of the proposed method to power assist systems.

In this paper, we propose a power assist system that amplifies sinusoidal human's torque and attains minimization of control input requirement using an impedance control and resonance. This impedance control is designed to realize the following features: 1) sinusoidal torque amplification. 2) Minimization of control input requirement by adjusting stiffness. 3) No requirement for the knowledge of amplitude, frequency and phase of human's torque. 4) No requirement for myoelectric signals. 5) Satisfaction of causality. Convergence of the proposed controller is proven theoretically. Simulation results verify the validity of the control scheme including some conditions not discussed in the theory. Experimental results show the validity of the control system including real human's complex dynamics and feedback loops

In the case of control for nonlinear mechanical systems, which have complex actuator dynamics, the total system becomes high-order and nonlinear. Generally speaking, it is not easy to tune feedback gains for state feedback. In this paper, we propose a feedback control scheme for motion control of nonlinear high-order systems. We prove that the proposed scheme can improve the trajectory tracking performance of a robot manipulator system with actuator dynamics. Moreover, some simulation results demonstrate the effectiveness of the proposed control scheme

This paper proposes power assist controllers that realize control input minimization using resonance of passive elements. To satisfy the objective, two types of systems are considered and controllers are proposed for each system. These controllers require no biosignals and satisfy causal manner. Convergence of the controllers is discussed theoretically. Simulation results show the validity of the proposed controllers. Experimental results show effectiveness of the proposed controller when the systems are used by a human operator

In this paper, a Virtual Power Limiter System is proposed. This requires no modeling and makes it possible to guarantee the stability of control systems which include unknown characteristics: flexibility in flexible manipulators, compressibility in pneumatic servo systems, human dynamics in man-machine systems, hardware nonlinearity in mechatronic systems, and so on. The details of the proposed virtual power limiter system and experimental verification with a man-machine system are presented.

In this paper, we propose a passivity monitor which evaluates stability of a system based on the concept of passivity, and a software limiter which turns the system stable if it is originally unstable. It is shown that asymptotic stability will be guaranteed for arbitrary robots with arbitrary control schemes and environments, even if their properties are unknown. The validity of the passivity monitor and the software limiter is verified by numerical simulations and experiments performed on various unstable systems.

In this paper, three fundamental techniques to improve laminated passive elements are proposed for wearable haptic displays. First, a new shape of sheet surfaces in laminated passive elements is introduced. Sliding motion between laminated sheets causes unexpected bad effect to static stiffness. An effective triangle shape for sheet surfaces, which prevents from sliding, has been analyzed. This technique improves the stiffness of laminated elements. Next, a binary stiffness control method is proposed. It realizes arbitrary stiffness in a certain resolution only by on/off air valves. A parameter designing strategy for linear stiffness change is also described. Last, a technique to realize controllable multi-dof constraints is introduced. It realizes a multi-dof module of laminated elements, so it is an essential technique for multi-dof haptic devices. The validity of all the proposed techniques has been verified by some preliminary experiments.

When we control a flexible manipulator based on a dynamic model, we need to estimate the state variables with accuracy. In the case of rigid manipulators, the state variables consist of joint angles and their velocities which are measured easily by encoders, potentiometers, tachometers, and so on. In the case of flexible manipulators, however, the state variables also include elastic deformations and their velocities due to flexibility. Here we focus on visual sensor to measure distributed state variables of flexible manipulators. First, we discuss a distributed state estimation method which uses discrete position information of markers attached on flexible links. Second, when we apply the virtual joint model to flexible manipulators, elastic deformations are expressed by virtual passive joint angles which are lumped. So we have to correspond the real elastic deformations to the virtual joint angles. We also discuss this transformation. Third, when we estimate the lumped state variables by the proposed method, it is possible to identify physical parameters of the dynamic model. Finally, some experiments were carried out to verify the effectiveness of the proposed method.

In this paper, the new concept of the dynamic singular configuration of flexible manipulators using the inverse dynamics method, we need to consider this dynamic singular configuration of flexible manipulators. Without considering it, the control around the dynamic singular configuration may become unstable. As an example, we derive the dynamic singular configuration of a 2-DOF planar flexible manipulator modeled by a virtual passive joint model. The characteristics of the dynamic singular configuration and the dynamic manipulability of flexible manipulators are discussed, and its experimental verification was performed.