Fuzzy control of autonomous vehicle navigation utilizing an electrostatic potential field

Hebert, T.; Tsourveloudis, Nikos C.; Valavanis, Kimon P.

doi:10.1109/cca.1998.728591

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…There exist several proposed solutions to the problem of autonomous mobile robot navigation in 2-D uncertain environments that are based on fuzzy logic [I], [2], evolutionary algorithms [3], as well as methods combining fuzzy logic with genetic algorithms [4] and fuzzy logic with electrostatic potential fields [5].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic based autonomous skid steering vehicle navigation

Doitsidis

Valavanis

Tsourveloudis

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292)

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A two-layer fuzzy logic controller has been designed for 2-D autonomous navigation of a skid steering vehicle in an obstacle filled environment. The first layer of the fuzzy controller provides a model for multiple sonar sensor input fusion and it is composed of four individual controllers, each calculating a collision possibility in front, back, left and right directions of movement. The second layer consists of the main controller that performs real-time collision avoidance while calculating the updated course to be followed by the vehicle. The two layer controller applicability and implementation is demonstrated through experimental results and case studies performed on a real mobile robot.

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Section: Introductionmentioning

confidence: 99%

Fuzzy logic based autonomous skid steering vehicle navigation

Doitsidis

Valavanis

Tsourveloudis

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292)

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“…Recently, several new and improved solutions to the mobile robot navigation problem in unknown environments based on fuzzy logic have been proposed [7]- [9]. There also exist methods combining fuzzy logic with other algorithms, such as genetic algorithms [10], electrostatic potential fields [11], [12], and neural networks [13], etc.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy logic-based reactive navigation algorithm for mobile robots

Yang

Moallem

Patel

Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005.

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In this paper, a novel algorithm based on sensory information is developed to address the problem of Goal Unreachable with Large Obstacles (GUWLO) found in fuzzy logicbased navigation algorithms for mobile robots. The GUWLO problem occurs when the absolute value of the target angle is large and the directions to the left (or right) are completely blocked. This is alleviated by interpolating a temporary target angle considering the surface feature of the obstacle in front of the robot. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness of the resulting fuzzy navigation system and its improved performance over conventional fuzzy-logic navigation algorithms.

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