We are developing a conceptual design for a power distribution line maintenance robot system using a CG (computer graphics) simulator and an experimental robot system. This system is a semi-autonomous robot system that performs tasks using task-level instructions. An operator directs the tasks, for example inserting a bolt into a hole, and clicks the work objects ldquoBoltrdquo and ldquoHolerdquo in the picture on the display with a mouse.

We investigate a practical semi-autonomous power distribution line maintenance robot system which performs jobs using task level directions. We are developing a CG (computer graphics) simulator for investigation of the conceptual design of our proposed robot system. This robot system has a vehicle, a boom, an approach arm, and left and right work arms. We teach the motions through a series of move commands for a task, and these commands are stored in a task knowledge database. The taught positions of the motions are expressed as task object coordinates. This paper describes the architecture and the performance of the CG simulator system, and provides an example of maintenance tasks. In simulations, we show that the task can be performed in different work environments using the same commands taught in the task object coordinate system for the sequence task, "install the switch gear"

In the case of conventional industrial robot systems, operators have to write robot-language programs for each type of workpiece. This is an onerous task, especially when each workpiece has a different shape. We propose a teaching-less robot system for the finishing of two-dimensional workpieces of various shapes and thicknesses using force control and computer vision. The robot system does not require shape information for the workpiece to be included in the CAD data or to be input by the operator. Each workpiece shape is acquired by segmenting edges into straight lines and circular arcs from the image data of the workpiece. The robot-language program for each workpiece is generated automatically from the workpiece shape data and finishing condition data. The effectiveness of the proposed method is verified by experiments using a newly developed robot system. In the system, the robot picks up a workpiece whose shape is not previously known on the workpiece stand by itself and carries out the finishing tasks using the automatically generated robot-language program. This method provides a compact and inexpensive finishing robot system which reduces the programming and workpiece-setting burden on the operators.

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.

We have developed a new unilateral master-slave hand system. The master system consists of a master arm which has a 3-DOF parallel link mechanism and a 3-DOF wrist mechanism, and a dataglove that is usually used for a virtual reality system. The slave system has a 6-DOF arm and a 16-DOF four-fingered hand. In general, a slave system is controlled by position with reference to a master system position. In this system, when an operator makes the slave system work on a complicated task, he must look at the slave carefully and let his arm and hand manipulate discretely. In the new master-slave system, each finger of the slave hand has a fingertip tactile sensor, and it is controlled by position and force. When an operator has knowledge of a task and handling objects and sets the slave fingertip stiffness, the operation can be performed easily by handling the master arm and hand to a rough position.

This paper presents a force controlled robot system for grinding, chamfering and polishing in machining plants. To facilitate easy operations, a task-oriented robot language and a force control method for following the edges of workpieces have been developed. In the task-oriented robot language, a task is declared first by a task name, a tool code and a tool center point. The tool center point is a position in contact with a workpiece. These indexes and the force control motion command determine the parameters for the force control of the robot. The workpieces for grinding, chamfering, and polishing almost always differ their setting positions, their sizes and/or their shapes, even when the workpieces are the same parts in a machine. To cope with the workpiece difference, a tool moment control method, a skip function, and a round function have been developed. Experiments on chamfering of the edges of a part in an injection molding machine are reported.

The authors are developing a multifingered robot hand which is modeled on a human hand. The aim is to identify the technologies necessary for this type of robot hand. The hand consists of 4 fingers, each with 4 joints actuated by DC motors via wires. The hand is attached to the tip of a 6-degree-of-freedom arm. The fingers and the arm are controlled by 6 32-bit microprocessor boards. Each finger has a tactile sensor on the fingertip. This consisting of a silicone rubber cap with a cavity filled with an incompressible fluid. Using these sensors and potentiometers mounted at one side of each joint, contact forces and positions of the fingertips are controlled. Three or four fingers grasp an object cooperatively when each finger is force-controlled using the tactile sensors independently. Evaluation tests of the position and the force control were executed, and experiments requiring the robot hand to pick up a pen and write characters were conducted.

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.