Path planning is a key element in navigation of a mobile robot. Several algorithms such as a gradient method have been successfully implemented so for. Although the gradient method can provide the global optimal path, it computes the navigation function over the whole environment at all times, which result in high computational cost. This paper proposes a high-speed path planning scheme, called a gradient method with topological information, in which the search space for computation of a navigation function can be remarkably reduced by exploiting the characteristics of the topological information reflecting the topology of the navigation path. The computing time of the gradient method with topological information can therefore be significantly decreased without losing the global optimality. This reduced path update period allows the mobile robot to find a collision-free path even in the dynamic environment.

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of unpaved trail are included in this paper.

Optical coherence tomography (OCT) is high resolution medical imaging system which is obtaining image inside biological objects with non-destructive method. OCT system is based on Michelson interferometer with a reciprocating mirror in the reference arm and a biological object in the sample arm. The obtained OCT image suffers from a granular or mottled image, called speckle. Speckle is caused by random interferences between reflected coherence waves. In this paper, we propose effective speckle reduction method that uses wavelet transform. With wavelet domain image, sub-windowing and thresholding are performed. Finally, speckle reduction experiments for Misgurnus mizolepis skin and rat eye images are shown.

Support vector machines in biped humanoid robot are presented in this paper. The trajectory of the ZMP in biped walking robot poses an important criterion for the balance of the walking robots but complex dynamics involved make robot control difficult. We are establishing empirical relationships based on the dynamic stability of motion using SVMs. SVMs and kernel method have become very popular method for learning from examples. We applied SVM to model the practical humanoid robot. Three kinds of kernels are employed also and each result has been compared. As a result, SVM based on kernel method have been found to work well. Especially SVM with RBF kernel function provides the best results. The simulation results show that the generated ZMP from the SVM can be improve the stability of the biped walking robot and it can be effectively used to model and control practical biped walking robot.

It is necessary to improve the exactness and adaptation of the working environment for the intelligent robot system. The vision sensor have been studied for a long time at this points. However, it has many processes and difficulties for the real usages. This paper proposes a visual servoing in the virtual environment to support OLP(Off-Line-Programming) path compensation and supplement the problem of complexity of the old kinematical calibration. Initial robot path could be compensated by pixel differences between real and virtual image. This method removes the varies calibrations and 3D reconstruction process in real working space. To show the validity of the proposed approach, virtual space servoing with stereo camera is carried out with WTK and openGL library for a KUKA-6R manipulator and updated real robot path.

A new model for the continuous-magnetic interferences has been proposed in this paper to remove external interferes of magnetic field to the dual electric compass. By this removal, the dual electric compass can be used for proving the azimuth angle in an automobile navigation system instead of the rate gyroscope. In the navigation system with a GPS receiver, a DR sensor such as a rate gyroscope is needed to overcome the shielded areas, which is relatively expensive and requires frequent calibrations. However the dual electric compass designed by this research is cheap and provides absolute azimuth angle precisely, which is beneficiary to be used as a DR sensor. The main contribution of this paper is that the long-lasting magnetic interferences have been removed out by using the proposed model, which never be studied before. With a hybrid navigation system using a DR sensor, we demonstrated that dual electric compass is better than a rate gyroscope in terms of both economics and performances.

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

This paper describes a design experience of a low-cost 6 DOF spatial tracker system where relative low accuracy and relatively long ranges, wireless communication will be achieved by means of low cost accelerometers and gyros with contemporary microprocessor. However, there are two key problems; one is the bias drift problem and the other is that single or double integration of acceleration signal suffers not only from noise but also from nonlinear effects caused by gravity. To be specific, beginning and stopping of hand motions needs to be accurately detected to initiate and terminate integration process to get position and pose of the hand from accelerometer and gyro signals, since errors due to noise and/or hand-shaking motions accumulated by integration processes. Several experimental results are shown to validate our proposed algorithms.

Object recognition in the field of robotics generally has depended on a computer vision system. Recently, RFID(Radio Frequency IDentification) has been suggested as technology that supports object recognition. This paper, introduces the advanced RFID-based recognition using a novel tag which is named a 3D tag. The 3D tag was designed to facilitate object recognition. The proposed RFID system not only detects the existence of an object, but also estimates the orientation and position of the object. These characteristics allow the robot to reduce considerably its dependence on other sensors for object recognition. In this paper, we analyze the characteristics of the 3D tag-based RFID system. In addition, the estimation methods of position and orientation using the system are discussed.

In this paper, we consider the problem of designing sliding surfaces fur a class of dynamic systems with mismatched uncertainties in the state space model. In terms of LMIs, we give necessary and sufficient conditions fir the existence of a linear sliding surface such that the reduced order sliding mode dynamics is asymptotically stable and completely independent of uncertainties. We parameterize all such linear sliding surfaces by using the solution to the given LMI conditions. And, we consider the problem of designing linear sliding surfaces guaranteeing pole placement constraints or <TEX>$H_2/H_infty$</TEX> performances. Finally, we give a design example in order to show the effectiveness of our method.