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Integrating fuzzy topological maps and fuzzy geometric maps for behavior‐based robots
Author(s) -
Aguirre Eugenio,
González Antonio
Publication year - 2002
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10025
Subject(s) - computer science , robot , grid reference , motion planning , abstraction , fuzzy logic , metric (unit) , artificial intelligence , grid , representation (politics) , metric map , plan (archaeology) , topology (electrical circuits) , data mining , mobile robot , metric space , mathematics , geography , engineering , philosophy , operations management , law , mathematical analysis , archaeology , geometry , epistemology , political science , politics , convex metric space , combinatorics
In behavior‐based robots, planning is necessary to elaborate abstract plans that resolve complexnavigational tasks. Usually maps of the environment are used to plan the robot motion and to resolve thenavigational tasks. Two types of maps have been mainly used: metric and topological maps. Both types presentadvantages and weakness so that several integration approaches have been proposed in literature. However, in manyapproaches the integration is conducted to build a global representation model, and the planning and navigationaltechniques have not been fitted to profit from both kinds of information. We propose the integration of topologicaland metric models into a hybrid deliberative‐reactive architecture through a path planning algorithm basedon A * and a hierarchical map with two levels of abstraction. The hierarchical map containsthe required information to take advantage of both kinds of modeling. On one hand, the topological model is basedon a fuzzy perceptual model that allows the robot to classify the environment in distinguished places, and on theother hand, the metric map is built using regions of possibility with the shape of fuzzy segments, which are usedlater to build fuzzy grid‐based maps. The approach allows the robot to decide on the use of the mostappropriate model to navigate the world depending on minimum‐cost and safety criteria. Experiments insimulation and in a real office‐like environment are shown for validating the proposed approach integratedinto the navigational architecture. © 2002 Wiley Periodicals, Inc.