In this paper, we propose an idea which can solve the complexity of the overlapping situation observed in control system of living things. We introduce an another element between controlled object and control law. This newly introduced element is named as Implicit Control Law and decided by interaction of the controlled object, the control law and the field. Furthermore, the Implicit Control Law does not only solve the indivisibility problem but also produces a start point for understanding of realtime environmental adaptation function of living thing with tiny brain. That is, the Implicit Control Law is a core principle of Mobiligence.

This research project, as a part of special project for earthquake disaster mitigation in urban areas initiated by the MEXT, aims to extend the existing robotics and human interface technologies and to establish a novel human-machine interacting structure to enable effective use of semi-autonomous robots in place of humans for searching survivors from rubble under human remote instructions. Collaboration and coordination of the human and robot intelligence and skills are to be developed from both hardware and software viewpoints to make the results of this project contribute to improvement of the search technology, an important issue in the urban robot-assisted search and rescue activities. Research efforts and results are described in this paper.

Concepts and necessity of a dummy (human model) which can simulate a disaster victim for the purpose of evaluating rescue equipments including robots and rescue skills of human and robots are proposed. By contrast of conventional dummies in various fields, the concrete requirements are made clear. The plan of research and development project based on the concept is described. In the latter part of this paper, the 1st prototype under development is introduced. It is based on a human model (doll) for training of bathing assistance, and is equipped with 8-channel telemetric sensors, a wireless camera, a voice recorder, a heater vest, and a carbon dioxide gas tank.

A learning and dynamic pattern generating system for acquiring the skills in dynamic manipulation of objects using robotic manipulators is to be established, where the desired space trajectories for the manipulators are not specified explicitly. Robotic batting is taken as a task example. The problem is approached so as to result in an iterative learning of the joint driving torque patterns of the manipulator that are considered as the task skills and learned against several typically given desired ball velocities. A multi-layered artificial neural network is used to learn and generalize the joint driving torque against various desired ball velocities, and an iterative optimal control algorithm is adopted to generate the supervisory joint driving torque signals for the neural network. Computer simulation examples of a three-degree-of-freedom manipulator are outlined, the results are depicted to explain the idea and verify the proposed approach, and the robustness issues are discussed qualitatively.

In this paper, we propose a direct torque control method for the prosthetic hand. In order to estimate the joint torque from EMG signals, an artificial neural network by the feedback error learning schema is used. 2-DOF motions, i.e. hand grasping/opening and arm flexion/extension, are picked up. In the experiments, two measurement conditions of EMG signal are prepared: the forearm from which the EMG signal is measured is free or fixed. Then it is verified that the neural network can learn the relation between the EMG signal and the joint torque under these two measurement conditions.

Dynamic control of a three-fingered robot hand manipulating an object in 3D space, while allowing one of the three fingers to slide in order to change its grasp location on the object surface, is formulated. The static and dynamic friction between the sliding finger and the object surface are explicitly considered and their effects regarding the behavior of the finger and object 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 have useful application to a multifingered robot hand in performing certain tasks involving the re-grasping and re-orientation of an object without interrupting the grasp.

Traditionally, tasks for a robotic system are specified by a desired timed trajectory. There, however, are many tasks in which the desired motions are specified by the state of system rather than time, such as contour following tasks. For such tasks, passive velocity field control (PVFC) has been proposed and the geometry of the controlled systems was analyzed. In this paper, a method to apply the PVFC to cooperative multiple mobile robotic systems whose sub-system is under nonholonomic constraints and which convey a common rigid object in a horizontal plane is proposed, and the effectiveness of the control method is demonstrated by several numerical simulations.

Task-oriented motion skill formation for kinematically redundant robot manipulators as an alternative approach to their task planning and control problem, is discussed. Elasto-viscous structures analogous to human arm muscle-skeleton structures are assumed to be the base of the joint actuation, and their dynamic impedance properties (stiffness and viscosity), together with their equilibrium trajectory profiles, are defined as the task skill. An iterative computing algorithm based on variant calculus is derived, and task examples on a 3 DOF planar manipulator are presented.

Traditionally, tasks for a manipulator are specified by a desired timed trajectory. There, however, are many tasks in which the desired motions are specified by the state of system rather than time, such as contour following tasks. For such tasks, passive velocity field control (PVFC) has been proposed and the geometry of the controlled systems was analyzed. In this paper, a method to extend the PVFC to cooperative multiple manipulators is proposed, and the effectiveness of the control method is demonstrated by numerical simulations, and some properties are shown.

A display system for displaying feel information while manipulating dynamic virtual objects is introduced and new concept of impedance display is proposed. An unified description of the dynamics of virtual objects based on the Lagrangian formulation is derived. The detection of the grasp states, and the friction effects at the grasp points on virtual object surface, which is important to help recognize the object and handle it more dexterously, are treated explicitly. Display algorithms which create and present the dynamic operating feel of an object as well as the friction feel on the object surface to the operator is provided. Experimental verification on the proposed approaches is performed and its results are outlined.>

A cooperative dynamic hybrid position/force control method for a set of robot arms or a multifingered robot hand handling a single object with or without its motion being constrained by its environment is shown. The method takes the manipulator dynamics and object dynamics into consideration and controls the motion of an object under constraint as well as constraint force when the object motion constraint and the internal force occur. The motion control of an object in free space can be treated as the case of no constraint on object motion in the formulation. An unified description for accommodating various grasp types is used. Several experimental results are presented that show the validity of the proposed approach.>

A cooperative dynamic hybrid control method for multimotion robotic mechanisms handling a single object whose motion is constrained by environment is discussed. This method takes the manipulator dynamics and object dynamics into consideration and is for controlling the motion of the object as well as for controlling the constraint force and the internal force. The following results are obtained: (1) the force and kinematic relations are established for arms grasping and manipulating an object using various types of end effector; and (2) using the first result, a nonlinear state feedback law for the joint driving force that linearizes and decouples the robot system with respect to the object motion, constraint force, and internal force is given. A basic structure of the dynamic hybrid control system with a servo compensator is presented. The effectiveness of the proposed approach has been examined by a simple experiment. These results are useful for the fine manipulation of an object, in the sense that one can specify the controller characteristics independently for the individual specification of the object motion, the interaction between the object and its environment, and the grasping of the object.>