We developed a robot system which can play one-on-one volleyball games with a human player. It can not only hit a flying ball back to the player correctly but also have various autonomous functionalities to interact with humans necessary for playing games, i.e., it can pick up a ball of a requested color by recognizing voice instructions, can locate the players by recognizing their faces, and can shake hands. This robot performed the entire game sequence over 100 times at a company-sponsored exhibition, where the ball rally continued over 25 times with an arbitrary player. In this paper, we mainly describe the real-time visual feedback system of the robot which is essential for playing ball games.

As an initial stage in the realization of an autonomous robot system for the construction of overhead distribution lines, we have developed an experimental setup with a task planner to install a power switchgear model on a mock-up utility pole. When an operator inputs a task level command of a standard installation task to the system, the task planner generates robot control commands to perform the desired task automatically by referring to the environment and the task knowledge database. The robot then moves and executes the specified task according to the control commands that have been generated. We have verified in the experimental setup that, using the developed task planner a number of typical task for installation of the power switchgear model can be performed smoothly with a small amount of assistance from the operator.

For part III, see ibid., pp. 1237-1244. A simple stiffness control method for a seven-degree-of-freedom redundant robot arm is presented. The method is very practical method for application to a real robot system. The robot arm is able to move compliantly by this method without heavy computation. The method uses the transpose of the Jacobian matrix to transform the end-point forces into the joint torques for force feedback, but does not require either inverse of the Jacobian matrix or solution of the kinematic equation. Also, the method uses the "joints potential" but does not require pseudo-inverse of the Jacobian matrix to keep the configuration of an arm even if the arm is redundant. The authors have applied this control method to their dual experimental robot arms. Both arms are anthropomorphic and have seven degrees of freedom except for the one degree of freedom of the gripper and are part of the model-based remote maintenance robot system TAROS (Toshiba Advanced Robot System). The arms were able to carry out compliantly such tasks as turning a crank or fastening a bolt and to grope on the surface of the work object and locate the positions of holes.

For part I, see ibid., pp.1225-1230. The authors are developing a model-based remote maintenance robot system which autonomously carried out maintenance tasks in nuclear facilities, for example nuclear power plants and nuclear fusion reactors. Two measurements methods for the robot system are described: one is a laser range finder, and the other is a groping method for the target tasks of inserting a bolt and setting a nut. In the groping method, an arm with a bolt gropes on the flange surface, and a rapid change in the force signal is detected when the bolt tip comes across a hole. Position measurements are made by the joint angles in groping. Therefore, it has the same merit as direct teaching in industrial robots. The robot system has carried out inserting a bolt and setting a nut on a flange by using these methods.

Describes the outline of a model-based remote maintenance robot system for nuclear facilities such as nuclear power plants and nuclear fusion reactors. This robot system aims at autonomously carrying out maintenance tasks which the operator directs by task-level commands, for example, "set flange" and "set valve". This robot system is composed of a device for measuring the position of the object to be handled, a task planner which generates the robot control program from the task-level command, and an arm controller which moves the arm under either position or stiffness control according to the generated program. In experiments, the robot system carried out the insertion of a bolt and the setting of a nut on a flange.

For part II, see ibid., pp. 1231-1236. Introduces a task planner for the model-based remote maintenance robot system called TAROS (Toshiba Advanced Robot System). TAROS's task planner has a task knowledge database describing procedures for performing the desired tasks and an environmental knowledge database describing geometrical characteristics and arrangement data for the objects to be handled. These data are represented by frames. When the operator inputs a task command, the task planner generates robot control programs automatically by referring to the databases. In the task planning, even though object's position or orientation data in the environmental knowledge database include errors, suitable motions are selected from the task knowledge database according to the number of errors, and executed. Thus a desired task can be performed easily without making a detailed robot control program in which the object's position and orientation errors are taken into consideration. It was verified that the fastening and loosening operations for a nut and a flange bolt were performed autonomously by using the task planner of TAROS.

A novel approach to the teaching of skills that human workers have acquired in performing specific tasks is presented. A skilled worker shows how to perform a given task, and his motions are measured. The force exerted by the worker and the displacement of the tool manipulated by the worker are monitored and stored in a computer. The data are analyzed to find the control law of the human expert. The functional relationship between the force and the displacement is derived from the data by using a curve-fitting technique. The identified relationship is used as a reference model for controlling a manipulator arm to replicate the expert motion. The method is applied to the impedance control of a simple grinding robot.>