Proceedings of the IEEE SoutheastCon 2000. 'Preparing for the New Millennium' (Cat. No.00CH37105)
DOI: 10.1109/secon.2000.845425
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Fuzzy motion planning using the Takagi-Sugeno method

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Cited by 5 publications
(5 citation statements)
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“…Hex Moor [44] was the frst to apply the FL concept to robotic route planning and obstacle avoidance. Te Takagi-Sugeno technique was then used to construct fuzzy robot motion planning [45]. Similarly, in [46], fuzzy robot motion planning was proposed utilizing the genetic algorithm with a fuzzy critic.…”
Section: Heuristic Approachmentioning
confidence: 99%
“…Hex Moor [44] was the frst to apply the FL concept to robotic route planning and obstacle avoidance. Te Takagi-Sugeno technique was then used to construct fuzzy robot motion planning [45]. Similarly, in [46], fuzzy robot motion planning was proposed utilizing the genetic algorithm with a fuzzy critic.…”
Section: Heuristic Approachmentioning
confidence: 99%
“…A considerable amount of publications are aimed to develop robot motion planning [1]. Early and influential work on motion planning include algorithms for path planning [2] as well as approaches based on fuzzy logic [3], [4], genetic algorithms [5], [6], and neural networks [7], [8].…”
Section: A Motion Planningmentioning
confidence: 99%
“…A Sugeno-type [6], fuzzy motion planner of four inputs one output is introduced to give an obstacle-free direction to the robot controller. The inputs are the frontal, right and left obstacle ranges found by the front, right and left sensors.…”
Section: Design and Simulation Of The Layered Fuzzy Navigatormentioning
confidence: 99%
“…The fuzzy motion planner uses Takagi-Sugeno fuzzy inference for the rule evaluation [6,17,18]. Unlike other fuzzy control methods [19], the Takagi-Sugeno results in the output of a control function for the system depending on the values of the inputs which is ideal for acting as an interpolation supervisor of multiple linear controllers that are to be applied, respectively, to different operating conditions of a dynamic nonlinear system as in the present case.…”
Section: Design and Simulation Of The Layered Fuzzy Navigatormentioning
confidence: 99%
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