Physically Based Simulation Model for Acoustic Sensor Robot Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A New Navigation Method for an Automatic Guided Vehicle
Journal of Robotic Systems
Comparison of Khepera robot navigation by evolutionary neural networks and pain-based algorithm
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Mobile robot navigation in 2-D dynamic environments using an electrostatic potential field
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Dynamical neural networks for planning and low-level robot control
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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In this paper, an obstacle avoidance method for wheeled mobile robots is proposed, based on selection of the local target points of robot's movement called “via-points” which are defined in a navigation space, generated by taking into consideration a smooth robot motion. The proposed algorithm utilizes a fuzzy multi-attribute decision-making method in which three fuzzy goals are defined to achieve successful robot navigation by deciding the via-point the robot would proceed at each control step. Via-point is defined as the local target point of a robot's movement at each decision instance. Three fuzzy goals to achieve successful robot navigation are defined. At each decision step, a set of the candidates of a next via-point in a 2D navigation space is constructed by combining various heading angles and velocities. Given the fuzzy goals, the fuzzy decision making enables the robot to choose the best via-point among the candidates. An efficient scheme for local minimum recovery from trapped-in situation is also provided. A series of simulations has been performed to study the effects of associated navigation parameters on the navigation performances. The method has been implemented on an actual mobile robot and experimented in real environments. Results from a series of simulations and experiments conducted in real environments show the validity and effectiveness of the proposed navigation method.