Local map building for mobile robot autonomous navigation by using a 2D laser range sensor

Local map building for mobile robot autonomous navigation by using a 2D laser range sensor

Abstracts 135 175 Decision in Complex Environment: Integrate Quantita~ive Model with Qualitative Judgement ShiJing Zhu, Ting Chen, pp 807-810 180 G...

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Abstracts

135

175 Decision in Complex Environment: Integrate Quantita~ive Model with Qualitative Judgement ShiJing Zhu, Ting Chen, pp 807-810

180 Genetic Model of an intelligent Sensor Using the Object Oriented Paradigm J.F. Figueroa, P.P. EgUi, pp 831-834

Decision making in complex environments is considered, and an approach integrating a quantitative decision model with qualitative judgement is proposed. The concept of degree of belief for a quantitative decision model in a eomplex environment is presented. The integration of the formalization and reasoning of the quantitative model with qualitative judgement is studied. The combination of various degrees of belief generated by the quantitative model and the quafitative judgement is discussed. A decision rule for trade-offs between optimality and degree of belief of optimality is proposed

A novel approach to modelling generic intelligent sensors is presented. The degree of intelligence incorporated in the sensor is related to the following functional characteristics: interpretation of sensed values, estimation of future values or behaviour, and learumg of the sensor's own behaviour and evolution, so it may update its ability to interpret and estimate, and always provide current, accurate and complete information. The object-oriented paradigm is used to implement the model, using Smalltalk/v as the object-oriented environment. A model structure has been created and tested by instantiating simple versions of two intelligent sensors: a flowmeter and a frequency meter.

176 Multtfrequency Binary Testing with Phase and Frequency Shift Keyed Modulation LA. Henderson, J. McGhee, pp 811-814

181 Local Map Building for Mobile Robot Autonomous Navigation by Using a 2D Laser Range Sensor J. Gonzalez, A. Ollero, P. Hurtado, pp 835-838

Microcomputer binary signals are required for multifrequency binary testing of control systems. Symbolic descriptions of digital shift-keyed modulation using compact binary codes are highlighted as the basis of signal engineering techniques to design new multifrequency binary sequences (MBS) test signals. Their energy may be concentrated in harmonic arrays which measure specified spectral information. Phase-shift keyed MBS signals are designed with a zoom attribute to identify narrowband frequency information with a high speOxal resolution. Frequency-shift keyed MBS use an extended range attribute to evaluate wideband frequency information. The application of these test signals is illustrated by two examples.

This paper describes a method of building the map of the environment for a given pose of a mobile robot Oocal map). The information is provided by a two-dimensional laser range finder that scans radially, parallel to the ground. From this, the local map builder produces a set of (typically) short line segments that can approximate the shape of any kind of environment, adapt to curved profiles, and provide an easy and precise model of any type of environment. Major concerns addressed in this paper are robustness against spurious noise, noise cleaning, range data clustering, and line segment fitting. Real data is used to demonstrate the system's performance.

177 On-lAne Multiple Component and Instrument Fault Diagnosis in Dynamic Systems M.N. Barkesseh, N.A. Kheir, pp 815-821 This paper presents a methodology, for on-line implementation, to diagnose failure(s) occurring in physical plant component(s) and/or iustrument(s). This methodology allows for the detection of component faults by a bank of matched filters. The detection of instrument failures is accomplished by a bank of full-order Luenberger observers. A rule-bnsed technique is also developed and used to identify a failure. Simulation results for an aircraft model have shown that this diagnostic aplx~ach is applicable to a large number of fnilores, and the action to remove these failures is also possible via an automated process.

178 Using Condition Monitoring to Enhance Robot Position Control A. Start, R.J. Wynne, I. Kennedy, pp 823-826 The umeliability of automated robotic plants has led to an investigation of the causes of robot-related failures in such plants. Positioning and related problems are identified as the principle cause of robot down-time, and indicate the requirement for an online monitoring system. A digital photogrammetry approach was adopted, using a portable PC with image-processing hardware/software and CCD cameras. The system is used to make periodic checks on the positioning of the robot during normal operation, and the data is fed back to prevent quality degradation and subsequent line failure.

179 Fault Diagnosis in HVDC Systems with Neural Networks L.L. IAd, F. Ndeh-Che, K,S. Swamp, H.S. Chandrusekharalah, pp 827-830 This paper describes a neural-network design and its simulation results for fault diagnosis in HVDC power systems. Fault diagnosis is carried out by mapping input data patterns, which represent the behaviour of the system, to one or more fault conditions. The behaviour of the converters is described in terms of the time-varying patterns of conducting thyristors, pulse zone periods, voltage zone periods and ac and dc fault characteristics. A three-layer neural network consisting of 24 input nodes, 12 hidden nodes and 13 output nodes is used. Thirteen different faults were considered, and the neural-network approach shows a great potential as an effective method of fault diagnosis.

182 An lntemgent Supervisor for Adaptive Mode-Switch Control J. Van Amerongen, R.A. Hllhorst, P. Liilmberg, H.J.A.F. Tulleken, pp 839-842 An adaptive controller is described, based on the idea that information gathered when new controller settings are computed is not forgotten but stored in memory. If the same situation is encountered again, this information can be retrieved and used for immediate adjustment of the controller. Various methods of data storage and retrieval are discussed. Best results are obtained with a method which, from a number of models running parallel with the process, selects that which describes the present process behaviour most adequately. Experimental results with a flexible beam and with a two-link flexible robot arm demonstrate that this is an attractive alternative to conventional adaptive or robust control.

183 OBJECT-SEXI: Objects, Rules and Fuzzy Functions for Identification K. Szafnicki, S. Gentll, pp 843-846 The main aspects of an Object-Oriented knowledge-based system for process identification are presented. Its knowledge base relies on a mixed structxtre, implemented within an object-oriented representation, as well as modules of production roles. Objects allow easy implementation, updating and extension of the structured theoretical knowledge about models, transfer functions, polynomials, etc. Relatively small rule bases, attached to the slots of the objects, include the empirical knowledge about process identification. Fuzzy compatibility functions are used for the numerical-symbolic conversion of values supplied by the computations of the parameter-estimation module. The search strategy for an "optimal" model structure has been implemented within a dedicated meta-knowledge base.

184 Development of a Knowledge-Based Approach for RealThne Prodidive Process Control T.H. Lee, C.C. Hang, S. Nungam, pp 847-850 This paper presents a knowledge-bnsed approach to real-time predictive control which is appficable to a large class of industrial process-control problems. The class of processes considered are those where dead-time is significant, and the approach adopted is an integration of hard algorithms with knowledge-based methods. The paper also includes the results of real-time experiments for level control in a coupled-tank system.