Improved design methodology for an existing automated transportation system with automated guided vehicles in a seaport container terminal

In this paper, we propose an improved design methodology to meet the changing demands of an existing automated container transportation system in which automated guided vehicles (AGVs) are used. This system is called an AGV transportation system. To achieve an improved design, it is essential to detect and correct any occurring bottlenecks. For this purpose, we exhaustively enumerate design proposals by constructing a logic tree. As a case study to verify the proposed methodology, we apply the methodology to an existing AGV transportation system. From the enumerated design proposals, we suggest design policies by considering the actual constraints of the transportation system. Finally, we redesign the transportation system as rapidly as possible. On the other hand, we keep system balancing into account; then, we derive a suitable demand and input number of AGVs under given specifications for a transportation system.     

Meaningful conversation with mobile robots

We describe an implementation integrating a complete spoken dialogue system with a mobile robot, which a human can direct to specific locations, ask for information about its status and supply information about its environment. The robot uses an internal map for navigation, and communicates its current orientation and accessible locations to the dialogue system using a topological map as interface. We focus on linguistic and inferential aspects of the human–robot communication process. The result is a novel approach using a principled semantic theory combined with techniques from automated deduction applied to a mobile robot platform. Due to the abstract level of the dialogue system, it is easily portable to other environments or applications.     

PLC在转炉风机煤气回收中的应用与研究

介绍转炉一次除尘风机及煤气回收系统中应用的可编程控制器(简称PLC)系统，对系统调试生产过程中遇到的几个问题进行分析与研究，并提出建议和改进方法。     

Control System Design for an Upper-Limb Rehabilitation Robot

Control system implementation is one of the major difficulties in rehabilitation robot design. The purpose of our study is to present newly developed control strategies for an upper-limb rehabilitation robot. The Barrett WAM Arm manipulator is used as the main hardware platform for the functional recovery training of the past-stroke patient. Passive and active recovery training have been implemented on the WAM Arm. A fuzzy-based PD position control strategy is proposed for the passive recovery exercise to control the WAM Arm stably and smoothly to stretch the impaired limb to move along predefined trajectories. An adaptive impedance force controller is employed in the active motion mode in which a fuzzy logic regulator is used to adjust the desired impedance between the robot and impaired limb to generate adaptive force in agreement with the change of the impaired limb's muscle strength. In order to evaluate the change of the impaired limb's muscle power, the impaired limb's mechanical impedance parameters as an objective evaluation index is estimated online by using a recursive least-squares algorithm with an adaptive forgetting factor. Experimental results demonstrate the effectiveness and potential of the proposed control strategies.     

A Localization Algorithm for Autonomous Mobile Robots via a Fuzzy Tuned Extended Kalman Filter

The capability to acquire the position and orientation of an autonomous mobile robot is an important element for achieving specific tasks requiring autonomous exploration of the workplace. In this paper, we present a localization method that is based on a fuzzy tuned extended Kalman filter (FT-EKF) without a priori knowledge of the state noise model. The proposed algorithm is employed in a mobile robot equipped with 16 Polaroid sonar sensors and tested in a structured indoor environment. The state noise model is estimated and adapted by a fuzzy rule-based scheme. The proposed algorithm is compared with other EKF localization methods through simulations and experiments. The simulation and experimental studies demonstrate the improved performance of the proposed FT-EKF localization method over those using the conventional EKF algorithm.     

Concurrent Map Building and Behavior Learning for Navigation in Unknown Environments

In this paper, we report a robust and low-cost navigation algorithm for an unknown environment based on integration of a grid-based map building algorithm with behavior learning. The study focuses on mobile robots that utilize ultrasonic sensors as their prime interface with the outside world. The proposed algorithm takes into account environmental information to augment the readings from the low angular accuracy sonar measurements for behavior learning. The environmental information is obtained by an online grid-based map learning design that is concurrently operating with the behavior learning algorithm. The proposed algorithm is implemented and tested on an in-house-built mobile robot, and its performance is verified through online navigation in an indoor environment.     

Continuous cast width control using a data mining approach

Abstract

Twelve per cent chrome ferritic (non-stabilised) stainless steel cast at the continuous caster at Columbus Stainless exhibited notable differences in the width change between consecutive heats. The reason for these differences is related to the fact that the steel is in a dual phase region between austenite and ferrite during the solidification stages of the continuous casting process. A model was developed and is currently used as a production tool to predict the width change of a 12% chrome ferritic heat before it is cast based on heat composition. The strand width is altered based on the model predictions by changing the secondary cooling pattern. It was uncertain if the current model is the best suited for this application and a study was carried out using different but more advanced data mining techniques in an attempt to improve the existing model. It was found that advanced data mining techniques could not improve the original rule based model.     

Modelling and control of coiling entry temperature using interval type-2 fuzzy logic systems

Abstract

The set-up of the cooling water applied to the strip as it traverses the runout table in order to achieve the coiler entry temperature was made by an intelligent model implemented using interval type-2 fuzzy logic systems. The model uses as inputs the targets for coiling entry temperature, strip thickness, finish mill exit temperature and finishing mill exit speed. The experiments of this application were carried out for three different types of coil in a real hot strip mill. The results proved the feasibility of the system developed for coiler entry temperature prediction. Comparison with the online type-1 fuzzy logic based model shows that the proposed interval type-2 fuzzy logic system improves performance in coiler entry temperature prediction under the tested condition.     

Translating Structured English to Robot Controllers

Recently, Linear Temporal Logic (LTL) has been successfully applied to high-level task and motion planning problems for mobile robots. One of the main attributes of LTL is its close relationship with fragments of natural language. In this paper, we take the first steps toward building a natural language interface for LTL planning methods with mobile robots as the application domain. For this purpose, we built a structured English language which maps directly to a fragment of LTL.     

Indirect adaptive control of a two-wheeled vehicle with low-resolution input and output

The Programmable Logic Controller (PLC) is widely used in the industrial world, e.g. in manufacturing, chemical processing, materials handling, etc. The PLC-based control system can be regarded as a control system with low-resolution inputs and outputs. This paper presents a sophisticated control policy which can enhance the control performance for such a class of control system even if the complete information of the plant is not available. In particular, the case of existing uncertainty or perturbations in the input matrix is addressed. The key contribution of this paper is to clarify the identifiability condition for parameters included in the input matrix from measured low-resolution inputs and outputs. This investigation leads to the development of an indirect adaptive control policy with low-resolution inputs and outputs. Finally, the proposed indirect adaptive control policy is applied to the line-following control of a two-wheeled vehicle and its usefulness is demonstrated through experiment.