Motion control for mobile robot obstacle avoidance and navigation: A fuzzy logic-based approach

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dc.contributor.author Zavlangas, PG en
dc.contributor.author Tzafestas, SG en
dc.date.accessioned 2014-03-01T01:19:18Z
dc.date.available 2014-03-01T01:19:18Z
dc.date.issued 2003 en
dc.identifier.issn 02329298 en
dc.identifier.uri http://hdl.handle.net/123456789/15408
dc.subject Fuzzy logic en
dc.subject Local navigation en
dc.subject Obstacle avoidance en
dc.subject Omnidirectional mobile robots en
dc.subject On-line motion planning en
dc.subject.other Autonomous agents en
dc.subject.other Collision avoidance en
dc.subject.other Fuzzy sets en
dc.subject.other Motion control en
dc.subject.other Motion planning en
dc.subject.other Navigation en
dc.subject.other Online systems en
dc.subject.other Problem solving en
dc.subject.other Fuzzy motion planner en
dc.subject.other Goal seeking en
dc.subject.other Local navigation en
dc.subject.other Omnidirectional mobile robots en
dc.subject.other Mobile robots en
dc.title Motion control for mobile robot obstacle avoidance and navigation: A fuzzy logic-based approach en
heal.type journalArticle en
heal.identifier.primary 10.1080/0232929032000115100 en
heal.identifier.secondary http://dx.doi.org/10.1080/0232929032000115100 en
heal.publicationDate 2003 en
heal.abstract One of the ultimate goals of mobile robotics research is to build robots that can safely carry out missions in hazardous and populated environments. Most of today's commercial mobile devices scale poorly along this dimension. Their motion planning relies on accurate, static models of the environments, and therefore they often fail their mission if humans or other unpredictable obstacles block their path, To build autonomous mobile robots one has to build systems that can perceive their environments, react to unforeseen circumstances, and plan dynamically in order to achieve their mission. Thus, the objective of the motion planning and control problem is to find collision-free trajectories, in static or dynamic environments containing some obstacles, between a start and a goal configuration. It has attracted much research in recent years. In this context the term control has a broad meaning that includes many different controls, such as low-level motor control, and behaviour control, where behaviour represents many complicated tasks, like obstacle avoidance and goal seeking. This article describes an intelligent motion planning and navigation system for omnidirectional mobile robots based on fuzzy logic. Owing to its simplicity and hence its short response time, the fuzzy navigator is especially suitable for on-line applications with strong real-time requirements. On-line planning is an on-going activity. The planner receives a continuous flow of information about occurring events and generates new commands in response to the incoming events, while previously planned motions are being executed. The fuzzy-rule-base of the proposed system combines the repelling influence, which is related to the distance and the angle between the robot and nearby obstacles, with the attracting influence produced by the distance and the angular difference between the actual direction and position of the robot and the final configuration, to generate actuating commands for the mobile platform. It can be considered as an on-line local navigation method for omnidirectional mobile robots for the generation of instantaneous collision-free motions. This reactive system is especially suitable for real-time applications. The use of fuzzy logic leads to a transparent system which can be tuned by hand or by a set of learning rules. Furthermore, this approach allows obstacle avoidance and navigation in dynamic environments. The functioning of the fuzzy motion planner with respect to omnidirectional mobile robots and results of simulated experiments are presented. en
heal.journalName Systems Analysis Modelling Simulation en
dc.identifier.doi 10.1080/0232929032000115100 en
dc.identifier.volume 43 en
dc.identifier.issue 12 en
dc.identifier.spage 1625 en
dc.identifier.epage 1637 en

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