A decentralized control system for cooperative transportation by multiple non-holonomic mobile robots

In this paper, we propose a decentralized control system for transporting a single object by multiple non-holonomic mobile robots. Each agent used in the proposed system has two arms, which can steer around a joint offset from the centre point between two driving wheels. One of these mobile robots acts as a leader, who is assumed to be able to plan and to manipulate the omnidirectional motion of the object by using a resolved velocity control. Other robots, referred to as followers, cooperatively transport the object by keeping a constant relative position with the object using a simple PI control. Different from conventional leader–follower type systems that transport an object by multiple robots in coordination, the present followers can plan an action based on their local coordinate and need no absolute positional information. In addition, as a special case, a system consisting of only two robots is introduced, in which the follower robot not only has an arm length controller to follow the leader but also has a fuzzy controller as an avoidance controller to avoid obstacles or a posture controller to keep a desired posture of the object. Simulation results are given to demonstrate the good performance of the proposed systems.     

A Fuzzy Behavior-Based Control for Mobile Robots Using Adaptive Fusion Units

It is known that a behavior-based control approach is effective for acquiring an intelligent control system of robots. However, further improvements are required for making any behavior-based control system robust against changes in the environments. A module learning method has been applied in the framework of fuzzy behavior-based control to have an adaptive behavioral fusion. In this paper, an adaptive fusion strategy is proposed to adaptively select a cooperative fusion unit or competitive fusion unit, depending on the external sensor information. Some simulations are given to illustrate that the present control systems are flexible against the change of environments or untrained environments, compared to those with a conventional priority-based fusion unit.     

Chemical durability of a superconducting oxide YBa2Cu3Ox in aqueous solutions of varying pH values

The chemical durability of a superconducting oxide YBa₂Cu₃O _x in the aqueous solution was investigated as a function of pH value by measuring the amount of leaching of the cations in the solution by inductively coupled plasma (ICP) analysis. The chemical durability of YBa₂Cu₃O _x was very low in highly acidic solutions of pH ca, 1, where the cations were dissolved in the same cation ratio as that of the compound. In an ion-exchanged water and NaOH solution, barium ions were leached out preferentially and almost no yttrium and copper ions were leached out. When NH₄OH was used as a basic reagent, the amounts of barium ions leached out were higher than in the NaOH solution of the same pH value and the dissolution of copper ions was observed, unlike in the NaOH solution of the same pH value. These observations were explained in terms of the chemical stability of individual oxide components.     

Modular fuzzy-neuro controller driven by spoken language commands.

We present a methodology of controlling machines using spoken language commands. The two major problems relating to the speech interfaces for machines, namely, the interpretation of words with fuzzy implications and the out-of-vocabulary (OOV) words in natural conversation, are investigated. The system proposed in this paper is designed to overcome the above two problems in controlling machines using spoken language commands. The present system consists of a hidden Markov model (HMM) based automatic speech recognizer (ASR), with a keyword spotting system to capture the machine sensitive words from the running utterances and a fuzzy-neural network (FNN) based controller to represent the words with fuzzy implications in spoken language commands. Significance of the words, i.e., the contextual meaning of the words according to the machine's current state, is introduced to the system to obtain more realistic output equivalent to users' desire. Modularity of the system is also considered to provide a generalization of the methodology for systems having heterogeneous functions without diminishing the performance of the system. The proposed system is experimentally tested by navigating a mobile robot in real time using spoken language commands.     

Control of three-link underactuated manipulators using a switching method of fuzzy energy regions

In general, manipulators used for industry and in academic laboratories have actuators to drive each joint. On the other hand, underactuated manipulators handled by our research have some passive or free joints without actuators and brakes. We recently developed a switching method of fuzzy energy regions to control such manipulators. In such a method, it is necessary to design parameters related to energy regions and the gains of some partly stable controllers based on the computed torque method. Here, the switching method is applied for a three-link underactuated manipulator. We optimize such design parameters related to fuzzy energy regions by a genetic algorithm. The effectiveness of the present method is illustrated with some simulations. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Evolutionary Learning of a Fuzzy Behavior Based Controller for a Nonholonomic Mobile Robot in a Class of Dynamic Environments

This paper presents an approach for evolving optimum behaviors for a nonholonomic mobile robot in a class of dynamic environments. A new evolutionary algorithm reflecting some powerful features in the natural evolutionary process to have flexibility to deal with changes in the environment is used to evolve optimum behaviors. Furthermore, a fuzzy set based multi-objective fitness evaluation function is adopted in the evolutionary algorithm. The multi-objective evaluation function is designed so that it allows incorporating complex linguistic features that a human observer would desire in the behaviors of the mobile robot movements. To illustrate the effectiveness of the proposed method, simulation results are compared using a conventional evolutionary algorithm.     

Intelligent control for avoiding the joint limits of redundant planar manipulators

This article presents an intelligent control system for a redundant manipulator to avoid physical limits such as joint angle limits and joint velocity limits. In this method, a back-propagation neural network (NN) is introduced for the kinematic inversion of the manipulator. Since this inverse kinematics has an infinite number of joint angle vectors, a fuzzy-neuro system is constructed to provide an approximate value for that vector. This vector is fed into the NN as a hint input vector in order to guide the output of the NN within the self-motion. Simulations and a comparative study are made based on a four-link redundant manipulator to prove the efficacy of the proposed control system.     

The Impact of Duodenal Mucosal Vulnerability in the Development of Epigastric Pain Syndrome in Functional Dyspepsia

An unidentified cause of functional dyspepsia (FD) is closely associated with medication resistance. Acid suppression is a traditional and preferential method for the treatment of FD, but the efficacy of this treatment varies between epigastric pain syndrome (EPS) and postprandial syndrome (PDS): it is efficient in the former but not much in the latter. Transepithelial electrical resistance (TEER), a surrogate of mucosal barrier function, was measured under pH 3 and pH 5 acidic conditions using duodenal biopsy specimens obtained from the patients with EPS and PDS and asymptomatic healthy controls. The infiltration of inflammatory cells to the duodenal mucosa was accessed by immunohistochemical analysis. The duodenal mucosal TEER in EPS patients was decreased by exposure to the acidic solution compared to that of the controls and the PDS patients. The decrease in TEER of the EPS patients was observed even under pH 5 weak acidic condition and was correlated to degree of the epigastric pain. Moreover, the duodenal mucosa of EPS patients presented an increase in mast cells and plasma cells that expressed Ig-E. Duodenal mucosal vulnerability to acid is likely to develop EPS.     

Preparation of Aluminum Oxynitride and Nitride Spherical Powders Via Flame Synthesis Assisted by DC Arc Plasma

Spherical powders of aluminum oxynitride/nitride are directly prepared by flame synthesis in which oxygen serves as an indispensable reactant. Nonoxide powders are commonly nonspherical, and the particle sizes of these powders are less than submicrometers. The major limiting factors for the synthesis are the free energy, reaction temperature, and reaction rate. The innovative issue related to this flame technology that is assisted by plasma is the ambivalence of the reducing gas atmosphere over 1500 K. The chemical equilibrium calculated indicates that the plasma heating compensates for the lack of reaction temperature under a low-oxygen condition. This burner realizes a high-speed reaction with the help of the reactive species in the arcs.