Showing papers by "Keigo Watanabe published in 1998"

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.

Control of an omnidirectional mobile robot

Abstract: Holonomic or nonholonomic omnidirectional mobile robots are known to be constructed by applying a specialized wheel or mobile mechanism In particular, some representative control approaches are described for a holonomic and omnidirectional mobile robot with three lateral orthogonal-wheel assemblies The uses of resolved acceleration control method, PID method, fuzzy model method, and stochastic fuzzy servo method are highlighted

Fuzzy behavior-based control for a miniature mobile robot

Abstract: We have already developed a fuzzy behavior-based control system that combines the concept of subsumption architecture and fuzzy reasoning technique. When applying it to a mobile robot, the robot needs to have precise information such as distance and azimuth. We discuss how to construct the fuzzy behavior-based control system for a miniature mobile robot in the case when the robot can not often receive any information from sensors. In addition, we apply a virus evolutionary genetic algorithm with species to generating the fuzzy rule. The effectiveness of the proposed method is shown by simulations.

A Fuzzy-Neural Realization of Behavior-Based Control Systems for a Mobile Robot

Abstract: A fuzzy-neural realization of a behavior-based control system is described for a mobile robot by applying the soft-computing techniques, in which a simple fuzzy reasoning is assigned to one elemental behavior consisting of a single input-output relation, and then two consequent results from two behavioral groups are competed or cooperated. For the competition or cooperation between behavioral groups or elemental behaviors, a suppression unit is constructed as a neural network by using a sign function or saturation function. A Jacobian net is introduced to transform the results obtained from the competition or cooperation to those in the joint coordinate systems. Furthermore, we explain how to learn the present behavior-based control system by using a genetic algorithm. Finally, a simple terminal control problem is illustrated for a mobile robot with two independent driving wheels.

A New Evolution Strategy and Its Application to Solving Optimal Control Problems.

Abstract: Evolution strategies(ESs)are search algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems numericallyThe effectiveness and simplicity of ES algorithms have lead many people to believe that they are the methods of choice for difficult, real-life problems superseding traditional search techniquesHowever, the inherent strength of the ES algorithms largely depends upon the choice of a suitable crossover and mutation technique in their application domainsThis paper discusses a new ES in which both a subpopulationbased arithmetical crossover(SBAC)and a time-variant mutation(TVM)operator are usedthe SBAC operator explores promising areas in the search space with different directivity while the TVM operator exploits fast(but not premature)convergence with high precision resultsThus, a balance between exploration and exploitation is achieved in the evolutionary process with these combined effortsThe TVM also acts as a fine local tuner at the converging stages for high precision solutionsIts action depends upon the age of the populations, and its performance is quite different from the Uniform Mutation(UM)operationThe efficacy of the proposed methods is illustrated by solving discrete-time optimal control models which are frequently used in the applications

Position-based impedance control using fuzzy environment models

Abstract: Impedance control is one of the most effective force control methods for a robot manipulator in contact with an object. It should be noted, however, that a practical study on such a method has not been successfully applied to an industrial robot with 6 degree-of-freedom. A hybrid compliance/force control (HCC) in this field was suggested to deal with the practical problem, in which a desired damping coefficient is determined by repeating many simulations. To determine a suitable compliance without trial and error, we have already presented a tuning method which produces the desired time-varying compliance, giving the critical damping in contact with an object, by using the information on the inertia and Jacobian matrices. But the tuning method needs to measure the physical information of the environment. In this paper, to overcome the problem we propose a fuzzy environment model that can estimate each directional stiffness of the environments. The fuzzy environment model is composed of several fuzzy rules which are learned with genetic algorithms. Simulation results show that the proposed method is very effective for deciding the desired compliance without any complicated tuning and is very robust to the change of environment.

Stochastic fuzzy servo control using multiple linear dynamic models

Abstract: A fuzzy servo system is described for a system with noises by using a stochastic fuzzy control method with some linear dynamic models. The fuzzy servo approach is applied to the control of rotational angle for an omnidirectional mobile robot with three orthogonal-wheel assemblies. The stochastic fuzzy servo method and its modified method with a static evaluation on the model confidence are implemented for some simulations of the mobile robot. In particular, two improvement methods are shown for the case when a set of the prespecified linear models does not include a model comparable to the reference rotational angle.

Design of Optimal Servo Systems Based on Fuzzy Models for an Omnidirectional Mobile Robot.

Abstract: In this article we propose a design method of an optimal servo fuzzy system for an omnidir- ectional mobile robot. For the robot, it is considered that the nonlinearity of the dynamic system is mainly dominated by the rotational angle of the robot between the moving and absolute coordinate systems. In order to build the model-based fuzzy servo system, we first choose some representative rotational angles to simplify the nonlinear model to multiple linear models. Then, optimal type-1 and type-2 servo controllers are derived for the rotational control of the mobile robot. The servo gain matrices associated with the controllers are found by using the linear fuzzy models. Finally, we present the results of simulations and show how to use our method to control the omnidirectional mobile robot.

Coordinative motion control for different kind of manipulators using a fuzzy compensator

Abstract: We describe a coordinative motion control based on the master/slave method for different kinds of manipulators. The master side consists of a pantagraph-type two link manipulator driven by a torque command, whereas the slave side is an industrial manipulator driven by a position command with a force/torque sensor. It is difficult to maintain a desired contact force by only a master/slave method. To maintain a desired contact force, a compensative position command is generated by using fuzzy reasoning with the force sensor information. The effectiveness is verified by experiments.

Position-Based Impedance Control Using Fuzzy Environment Model Learned with GA.

Abstract: Impedance control is one of the most effective control methods for a robot manipulator in contact with an object. It should be noted, however, that a practical study on such a method has not been successfully applied to an industrial robot with 6 degree-of-freedom. Recently, a hybrid compliance/force control (HCC) in this field was suggested to deal with the practical problem, in which a desired damping coefficient is determined by repeating many simulations, or by trial and error. In this paper, we first propose a fuzzy environment model that can estimate the stiffness of environments and give a generation technique of fuzzy rules learned with genetic algorithms. To determine suitable compliance without trial and error, we next introduce a method that produces the desired timevarying compliance, giving the critical damping in contact with an object by using the information on the inertia matrix. Simulation results show that the proposed method is very effective for deciding the desired compliance without any complicated tuning and is very robust to the change of environment.

Development of an omnidirectional mobile robot with active dual-wheel casters

Abstract: (1998). Development of an omnidirectional mobile robot with active dual-wheel casters. Advanced Robotics: Vol. 13, No. 3, pp. 239-240.

Control of a Six-DOF Parallel Link Manipulator with Artificial Rubber Muscles by an Integral Type Stochastic Fuzzy Method

Abstract: A robust control approach is described for controlling the position and orientation of a six-DOF parallel link manipulator, in which one prismatic link consists of a rubber muscle actuator, so that the controlled object contains several nonlinear factors. The position of the link is also assumed to be measured by using a linear potentiometer. As a result, the associated measurement system contains some measurement noises. The control system is construted using a stochastic fuzzy controller with an integlator so as to remove a tracking error. To design the feedback gains of the stochastic fuzzy controller, a mmn-max control strategy is adopted to the systems, with unknown physical parameters. The effectiveness of the proposed method is illustrated by using some actual experiments.