This paper deals with the effects of robot population density on the emergence of circle formation in multiple robots system. Individual robot has a specific range of signal communication to detect other robots. According to the information about the location of one or two robots detected by the signal communication within the range, the robot takes an action such as proceeding forward or turning left/right at each time step. Implementing this action selection algorithm to each of the robots, we carry out the computer simulation of global behaviors in the multiple robots system, and we find that there exists a certain condition under which the circle formation emerges in the multiple robots system. To investigate the effects of the robot population involved and the size of the simulation area on the characteristics of the circle formation, the computer simulation was made and it clarified that the emergence of the circle formation in the multiple robots system is strongly influenced by the robot population density rather than to the robot population and the simulation area size.

Effective robot functions emerge from not only according to the level of system control, i.e., intelligence, but also according to the conformity between morphology, intelligence, task and environment. This paper investigates the relationship between robotic morphology and intelligence against task and/or environmental conditions and the characteristics of functions emerging in evolutionary robotic systems. The robotic system used in the study has a reconfigurable morphology and intelligence, which were designed by genetic programming. The robotic morphology is represented as a graph structure constructed from cells with motor and visual sensors, and the intelligence is a computer program defined by a parse tree. In this study, a simulation of a task in which the robot had to maintain a certain distance from an object was executed. The results clarify the importance of conformity between morphology and intelligence, and show that effective functions emerge as the result of such conformity between morphology, intelligence, task and environment.

We investigate quantitatively the characteristics of relationships between learning and the sensory dimension. In the task of a two-mobile robotic system composed of a driving body and 1-DOF prismatic arm, carrying a long bar horizontally along a sinusoidal wavy road while keeping the bar-support length constant, a sensory-motor coordination is acquired by the reinforcement learning. We find the following results: when the two-mobile robotic system executes the task, a cooperative behavior performed by the forward and backward locomotions is needed, and we find 8 sensory dimensions that are necessary and sufficient in perception of the state for the robotic system. The sensory contribution rate of each sensory dimension for the perception of the robotic state is defined. Also, the two-mobile robotics system which is only equipped with sensors of large sensory contribution rate, can acquire the robotic control for the cooperative behavior of forward and backward locomotions by the online learning.

Deals with an autonomous action-mode change in a behavior-based learning of the mobile robotic system, which is composed of two mobile robots consisting of a crawler and a one DOF arm. The task is to carry a long bar horizontally along a compound road keeping the bar-support distance constant. We propose an online learning method-STL (S-temperature based online learning). During the learning process, the robotic system can build up the state categorization in terms of two-dimensional sensory data (support length and support inclination). The robotic system can transit seamlessly between the learning process and the task-achieving process according to the internal state of the robotic system that is controlled by the S-temperature introduced into the STL. We show the effectiveness of STL by hardware robot experiments.

Deals with characteristics of cooperative transportation of a long bar along a wavy road by two mobile robots. The robot module has a crawler body and a single degree-of-freedom prismatic arm. The task is to carry a long bar at constant support height and support distance along a one-dimensional sinusoidal wavy road. Their position and arm length are cooperatively adjusted by a subsumption architecture (SSA) control scheme according to their position on the wavy road. The SSA control scheme showed a successful achievement of the given task in most cases but the two robots were trapped in an inevitable deadlock situation for a particular initial position. Addition of one rotational degree-of-freedom to the arm can solve the deadlock problem. Finally the paper discusses some fundamental issues about the relationship between robot-body configuration/morphology, kinematics/dynamics, and intelligence from the results obtained.

We are attempting to introduce a 3-dimensional realistic human-like animate face robot to interactive communication modality. The face robot can recognize human facial expressions as well as produce realistic facial expressions. For the face robot to communicate interactively, we propose a new concept of "Active Human Interface"; and we investigate the performance of real-time recognition of facial expressions by neural network (NN) and the expressionability of facial messages on the face robot. We find that the NN recognition of facial expressions and face robot's performance in generating facial expressions are of almost same level as that in humans. This implies a high potential for the animate face robot to undertake interactive communication with human.

This paper deals with a kinematic analysis of locomotive cooperation necessary for two mobile robots to carry a long bar along a general wavy road. The robots are assumed to be driven by a crawler mechanism and to have a single link arm which moves in a prismatic way. The robots have a task to carry a long bar keeping its height and length constant and its posture horizontal. The analysis of kinematic conditions done for a sinusoidal wavy road is expanded for a general wavy road and the authors find that there exist two kinds of cooperation mode: one is to change the direction of locomotion and the other is to alternate the robot role from "master" to "servant" and vis-vasa.

A new type of mobile pipeline maintenance robot has been designed to clarify the feasibility of lazy tongs mechanism for adaptation to various size pipelines. The robot basically consists of three modules with two joints between modules and can move straight and spirally along the surface of pipeline. The robot can change its arm length in order to move on the pipeline of various size from 25 A to 100 A, and pass over obstacles such as reducer, diffuser, flange and other plant equipment. The control of the robot is so complicated that the modified dual control mode is introduced using the coordinate transformation matrix. By calculating the position and attitude of the robot under the control mode, the manoeuvrability of passing over a reducer is shown with experimental results.

Deals with a computer simulation study of the cooperative behavior of multirobots for investigating the characteristics of swarm intelligence generated by multirobot system. Individual robots in the multirobot system are equipped with low-level intelligence to detect obstacles, steer, proceed, and undertake a hello-call communication. This paper first clarifies the characteristics of multirobot behavior under free traveling without hello-call communication and then the characteristics of hello-call communication with respect to message transmission power over whole member robots. Introducing a marker robot to the multi-robot system, the authors find that the multirobot system can generate a communication chain to be used for searching the route to their goal. They demonstrate the swarm intelligence of the multirobots system in the case of route-searching and show the effects of robot population on the swarm intelligence.

The dynamical self knowledge allocation method is presented for a distributed intelligent system. The authors apply the method to the cellular robotic system CEBOT, which is one of the distributed systems. They propose a new matrix notation, the knowledge-based structure matrix, to express the communication link and states of the knowledge allocation. They also propose a matrix notation for describing a given task, the task matrix. The efficiency of the dynamical self knowledge allocation method reduces the total system communication information volume.>

Describes the stability of a flexible robotic arm when its mathematical model contains parameter uncertainties. The authors employ the H/sub infinity / control method which includes the LQ optimal control, and is robust. To estimate the stability domain of a closed-loop system, one must find the rate at which the system matrix A and the control matrix B change when a parameter changes. These rates are difficult to find, because the elements of the matrices change nonlinearly when the parameter changes. They calculate the rates approximately and obtain the stability domain by using the Routh condition. They also show some simulation results, demonstrating that the modeled stability domain of the one-degree-of-freedom flexible arm can be enlarged by appropriately choosing the arbitrary matrices of the H/sub infinity / control law.>