This paper develops a control method for some generic formation tasks of multiple mobile robots with inaccurate sensor information. Inaccurate sensor information means that all the robots have only local sensors that cannot accurately measure absolute distances and directions of objects. That is, all the sensors have limitation on the range, and uncertainty in the values. Therefore, more robust and reliable control logic is proposed and implemented. The logic is developed considering generic situations and increasing the number of robots participating in the formation. Petri nets are used for modeling and design of the control logic, which can visualize the control models and make it easy to check the states of each robot. Physically homogeneous mobile robots are designed and built to evaluate the developed logic. Each robot is equipped with eighteen infrared sensors and a UHF transceiver module. The experiment results are analyzed quantitatively by using the data of the relative distances and angles between the robots. And the trajectories of the robots during the formation are also evaluated. The developed control approach is demonstrated with experiments to be successful and efficient for the formation of autonomous mobile robots.

In this paper, design of a 3-degree-of-freedom mobile robot with three caster wheels is performed. Initially, kinematic modeling and singularity analysis of the mobile robot is performed. It is found that the singularity can be avoided when the robot has more than two wheels on which two active joints are located. Optimal kinematic parameters of mobile robots with three active joint variables and with four active joint variables are obtained and compared with respect to kinematic isotropic index of the Jacobian matrix of the mobile robot which is functions of the wheel radius and the length of steering link.

We propose a new two-degree of freedom parallel mechanism for a haptic device and will refer to the mechanism as the SenSation. The SenSation is designed in order to improve the kinematic performanced and to achieve static balance. We use the panto graph mechanisms in order to change the location of active joints, which leads to transform a direct kinematic singularity into a nonsingularity. The direct kinematic singular configurations of the SenSation occur near the workspace boundary. Using the property that position vector of rigid body rotating about a fixed point is normal to the velocity vector, Jacobian matrix is derived. Using the vector method, two different types of singularities of the SenSation can be identified and we discuss the physical significance of each of the three types of singularities. We will compare the kinematic performances(force manipulability ellipsoid, kinematic isotropy) of the SenSation with those of five-var parallel mechanism. By specifying that the potential energy be fixed, the conditions for the static balancing of the SenSation is derived. The static balancing is accomplished by changing the center of mass of the links.

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has ben installed an engine for speech recognition and synthesis and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the obttom of robot to track odour sources. 3 optical sensors are also in cluded in the intelligent mobile robot, which is driven by 2 D. C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method. The preliminary results are promising that intelligent mobile robot, which has been developed, is applicable to service robot system for environmental monitoring, localization of odour source, odour tracking of hazardous areas etc.

Recently, service area has been emerging field f robotic applications. Even though assistant robots play an important role for the disabled and the elderly, they still suffer from operating the robots using conventional interface devices such as joysticks or keyboards. In this paper we propose an efficient computer interface using real-time eye-gaze tracking system. The inputs to the proposed system are images taken by a camera and data from a magnetic sensor. The measured data is sufficient to describe the eye and head movement because the camera and the receiver of a magnetic sensor are stationary with respect to the head. So the proposed system can obtain the eye-gaze direction in spite of head movement as long as the distance between the system and the transmitter of a magnetic position sensor is within 2m. Experimental results show the validity of the proposed system in practical aspect and also verify the feasibility of the system as a new computer interface for the disabled.

Teach pendant is the most widely used means of robot teaching at present. Despite the difficulties of using the motion command buttons on the teach pendant, it is an economical, robust, and effective device for robot teaching task. This paper presents the development of a force/moment direction sensor named COSMO that can improve the teach pendant based robot teaching. Robot teaching experiment of a six axis commercial robot using the sensor is described where operator holds the sensor with a hand, and move the robot by pushing, pulling, and twisting the sensor in the direction of the desired motion. No prior knowledge of the coordinate system is required. The function of the COSMO sensor is to detect the presence f force and moment along the principal axes of the sensor coordinate system. The transducer used in the sensor is micro-switch, and this intuitive robot teaching can be implemented at a very low cost.

In this paper, the open-loop state response of the two-time-scale systems by unified approach using the $\delta$-operator is presented with an example of the aircraft longitudinal dynamics. First, the $\delta$-operator system unifies both the continuous system and the discrete system simultaneously, and the $\delta$-operator approach improves the finite word-length characteristics. This saves more computing time than that of the discrete system. Second, the singular perturbation method by block diagonalization reduces the sizes and orders of the systems. This also reduces the floating-point operations (flops). The advantage of those two approaches is shown by comparing our results with the earlier ones in the illustrative example of the longitudinal motion of F-8 aircraft.

This paper deals with a design problem of a decentralized controller with a strongly connected two-input two-output multivariable system. To this end, we present a classical design approach which consists of two main steps: one is to decompose the multivariable plant into two single-input single-output systems by means of the Individual Channel Design (ICD) concept, the other is to design controller of each channel by the Coefficient Diagram Method (CDM) so that it satisfies, especially, time domain specifications such as settling time, overshoot etc.. A design procedure was proposed and then was applied to a 2$\times$2 hot rolling mill plant. Simulation results showed that the proposed method has excellent control performances.

Nonlinear pulse width modulation (PWM) controlled system is considered to achieve control performance of thruster controlled spacecraft. The actual PWM controlled motions occur, very closely, around the average model trajectory. Furthermore nonlinear PWM controller design can be directly applied to thruster controlled spacecraft to determine thruster on-time. Sliding mode control for attitude tracking of three-axis thruster-controlled spacecraft is presented. Simulation results are shown which use modified Rodrigues parameters and sliding mode control law to achieve attitude tracking of a three-axis spacecraft with thrusters.

Jeha Ryu Department of Mechatronics, Kwangju Institute of Science and Technology This paper presents an application of a robust adaptive control strategy to HexaSlide type six degrees-of-freedom parallel manipulators. The HexaSlide type parallel manipulators are characterized as an architecture with constant link lengths that are attached to moving sliders on the ground and to a mobile platform. The proposed control law is developed based on a simplified second order system dynamic equation in joint space with uncertain mass, damper, spring, and Coulomb friction terms. These uncertain parameters are updated by an adaptation law that is derived by Lyapunov stability theorem. A robust adaptive control law by using the boundary layer is designed for the purpose of compensating for the neglected dynamic effects of the mobile platform and the six moving links that are modeled as a disturbance term. Experimental results show good and fast tracking performance.

In this paper, we propose a simplified pollution adaptive mesh generation algorithm using singular elements. The algorithm based on the element pollution error indicator concentrate on boundary nodes. The automatic mesh generation method is followed by either a node-relocation or a node-insertion method. The boundary node relocation phase is introduced to reduce pollution error estimates without increasing the boundary nodes. The node insertion phase greatly improves the error and the factor with the cost of increasing the node numbers. It is shown that the suggested r-h version algorithm combined with singular elements converges more quickly than the conventional one.

Uncertainties are the main reasons of deterioration of contour control of industrial articulated robot arm. In this paper, a high-precision contour control method was proposed to overcome some main uncertainties, such as torque saturation, system delay dynamics, interference between robot links, friction, and so on. Firstly, each considered factor of uncertainties was introduced briefly. Then proper realizable objective trajectory generation was presented to avoid torque saturation from objective trajectory. According to the model of industrial articulated robot arm, construction of Gaussian neural network controller with considering system delay dynamic, interference between robot links and friction was explained in detail. Finally, through the experiment and simulation, the effectiveness of proposed method was verified. Furthermore, based on the results it was shown that the Gaussian neural network controller can be also adapted for the various kinds of friction and high-speed motion of industrial articulated robot arm.

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

This paper concerns with a receding horizon estimator (RHE) for discrete-time linear systems subject to constraints on the estimate. In solving the optimization for every horizons, the past all measurement data outside the horizon is discarded and thus the arrival cost is not considered. The RHE in the current work is a finite impulse response (FIR) structure which has some good inherent properties. The proposed RHE can be represented in the simple matrix form for the unconstrained case. Various numerical examples demonstrate how including constraints in the RHE can improve estimation performance. Especially, in the application to the unknown input estimation, it will be shown how the FIR structure in the RHE can improve the estimation speed.