Keigo Watanabe

Bio: Keigo Watanabe is an academic researcher from Okayama University. The author has contributed to research in topics: Mobile robot & Robot. The author has an hindex of 32, co-authored 720 publications receiving 5450 citations. Previous affiliations of Keigo Watanabe include Beijing Institute of Technology & National Institute for Materials Science.

A particle-swarm-optimized fuzzy-neural network for voice-controlled robot systems

Abstract: This paper shows the possible development of particle swarm optimization (PSO)-based fuzzy-neural networks (FNNs) that can be employed as an important building block in real robot systems, controlled by voice-based commands. The PSO is employed to train the FNNs that can accurately output the crisp control signals for the robot systems, based on fuzzy linguistic spoken language commands, issued by a user. The FNN is also trained to capture the user-spoken directive in the context of the present performance of the robot system. Hidden Markov model (HMM)-based automatic speech recognizers (ASRs) are developed, as part of the entire system, so that the system can identify important user directives from the running utterances. The system has been successfully employed in two real-life situations, namely: 1) for navigation of a mobile robot; and 2) for motion control of a redundant manipulator.

An exoskeletal robot for human shoulder joint motion assist

Abstract: We develop exoskeletal robots to assist the motion of physically weak persons such as elderly persons or handicapped persons. In our previous research (2001), a prototype of a two degree of freedom exoskeletal robots for shoulder joint motion assist have been developed. In this paper, we propose an effective fuzzy-neuro controller, a moving mechanism of the center of rotation (CR) of the shoulder joint of the exoskeletal robot, and an intelligent interface in order to realize a practical and effective exoskeletal robot for shoulder joint motion assist. The fuzzy-neuro controller enables the robot to assist a person's shoulder motion. The moving mechanism of the CR of the robot shoulder joint is used to fit the CR of the robot shoulder joint to that of the physiological human shoulder joint during the shoulder motion. The intelligent interface is realized by applying a neural network and used to cancel out the effect the human subject's arm posture change. The effectiveness of the proposed method was evaluated by experiment.

Evolutionary Optimization of Constrained Problems

Abstract: Although evolutionary algorithms have proved useful in general function optimization, they appeared particularly apt for addressing nonlinearly constrained optimization problems. Constrained optimization problems present the difficulties with potentially nonconvex or even disjoint feasible regions. Classic linear programming and nonlinear programming methods are often either unsuitable or impractical when applied to these constrained problems [76]. Unfortunately, most of the real-world problems often pose such difficulties. Evolutionary algorithms are global methods, which aim at complex objective functions (e.g., non-differentiable or discontinuous) and they can be constructed to cope effectively with these difficulties. There are, however, no well-established guidelines on how to deal with infeasible solutions. Contemporary evolution strategies usually use “death penalty” heuristic for infeasible solutions. This death penalty offers a few simplifications of the algorithm: for example, there is no need to evaluate infeasible solutions and to compare them with feasible ones. Fortunately, this method may work reasonably well when the feasible search space is convex and it constitutes a reasonable part of the whole search space. Otherwise, such an approach has serious limitations. For example, for many search problems where the initial population consists of infeasible individuals only, it might be essential to improve them [101]. Moreover, quite often the system can reach the optimum solution easier if it is possible to “cross” an infeasible region especially in non-convex feasible search spaces. This chapter deals with a new approach which will utilize a log-dynamic penalty function method in the NES algorithm [61, 62] that has been proposed and tested in the previous chapter.

Feedback Control of an Omnidirectional Autonomous Platform for Mobile Service Robots

Abstract: This paper proposes a feedback control scheme for an omnidirectional holonomic autonomous platform, which is equipped with three lateral orthogonal-wheel assemblies. Firstly, the dynamic properties of the platform are studied, and a dynamic model suitable for the application of control is derived. The control scheme constructed is of the resolved-acceleration type, with PI and PD feedback. The control scheme was experimentally applied to an actual mobile robotic platform. The results obtained show that full omnidirectionality can be achieved with decoupled rotational and translational motions. Omnidirectionality is one of the principal requirements for mobile robots designed for health-care and other general-hospital services.

An exoskeletal robot for human elbow motion support-sensor fusion, adaptation, and control

Abstract: In order to help everyday life of physically weak people, we are developing exoskeletal robots for human (especially for physically weak people) motion support. In this paper, we propose a one degree-of-freedom (1 DOF) exoskeletal robot and its control system to support the human elbow motion. The proposed controller controls the angular position and impedance of the exoskeletal robot system based on biological signals that reflect the human subject's intention. The skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been fused and used as input information of the controller. In order to make the robot flexible enough to deal with vague biological signal such as EMG, fuzzy neuro control has been applied to the controller. The experimental results show the effectiveness of the proposed exoskeletal robot system.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Robust Model-Based Fault Diagnosis for Dynamic Systems

Abstract: There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.