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Journal ArticleDOI

Collision-avoidance by fuzzy-logic control for automated guided vehicle navigation

Pai-Shih Lee, +1 more
- 01 Jan 1994 - 
- Vol. 11, Iss: 8, pp 743-760
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TLDR
A fuzzy approach to collision avoidance for automated guided vehicle (AGV) navigation is proposed, such that the AGV is guided from the starting point toward the target without colliding with obstacles.
Abstract
A fuzzy approach to collision avoidance for automated guided vehicle (AGV) navigation is proposed. Static obstacles with no a priori position information as well as moving obstacles with unknown trajectories are considered in this study. Intuitive and subjective human ideas of collision avoidance are modeled into fuzzy rules. Fuzzy logic is applied in the inference procedure for AGV navigation, such that the AGV is guided from the starting point toward the target without colliding with obstacles. Furthermore, the proposed method can also be used for the navigation of multiple AGVs, where each AGV must avoid other AGVs as well as obstacles in the environment. Simulation results are presented to show the feasibility of the proposed fuzzy approach. © 1994 John Wiley & Sons, Inc.

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Journal ArticleDOI

Neurofuzzy-Based Approach to Mobile Robot Navigation in Unknown Environments

TL;DR: A neurofuzzy-based approach is proposed, which coordinates the sensor information and robot motion together and can adequately sense the environment around, autonomously avoid static and moving obstacles, and generate reasonable trajectories toward the target in various situations without suffering from the "dead cycle" problems.
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A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation

TL;DR: A layered goal-oriented motion planning strategy using fuzzy logic is developed for a mobile robot navigating in an unknown environment and is implemented on a real mobile robot, Koala, and tested in various environments.
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A neuro-fuzzy controller for mobile robot navigation and multirobot convoying

TL;DR: Real-time implementations of autonomous mobile robot navigation and multirobot convoying behavior utilizing the NiF-T are presented, with only five rules used to train the wall following behavior, while nine were used for the hall centering.
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Development of advanced parking assistance system

TL;DR: This paper is the first to apply a multilevel driver assistance system in the development of a system to aid in the parking process and the results of lane and row parking experiments conducted using the prototype system are shown.
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Sensor-based fuzzy reactive navigation of a mobile robot through local target switching

TL;DR: Fuzzy reactive control, incorporating a local target switching scheme, is applied to the automatic navigation of an intelligent mobile robot in an unknown and changing environment.
References
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Journal ArticleDOI

Fuzzy logic in control systems: fuzzy logic controller. II

TL;DR: The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined and several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated.
Journal Article

Fuzzy logic in control systems : fuzzy logic controller. Part II

TL;DR: The fuzzy logic controller (FLC) based on fuzzy logic provides a means of converting a linguistic control strategy based on expert knowledge into an automatic control strategy.
Journal ArticleDOI

Fuzzy Set Theory and Its Applications

TL;DR: In this paper, a new book about fuzzy set theory and its applications is presented, which can be used to explore the knowledge of the knowledge in a new way, even for only few minutes to read a book.
Journal ArticleDOI

Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis

TL;DR: In this article, a fuzzy logic is used to synthesize linguistic control protocol of a skilled operator for industrial plants, which has been applied to pilot scale plants as well as in practical situations.
Journal ArticleDOI

Real-time obstacle avoidance for fast mobile robots

TL;DR: A real-time obstacle avoidance approach for mobile robots that permits the detection of unknown obstacles simultaneously with the steering of the mobile robot to avoid collisions and advance toward the target.