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This paper presents a new path planning method for mobile robots in unknown environments. The structure of the proposed algorithm is a hybrid fuzzy logic neural networks, and hence it benefits from the potentials of these two techniques. For modeling the mobile robot, the proposed system adopts the Braitenberg's automata models that were developed for agents. Wheels of the robot are represented by...
Tracking control is a fundamentally important issue for robot and motor systems, where smooth velocity commands are desirable for safe and effective operation. In this paper, a novel biologically inspired tracking control approach to real-time navigation of a nonholonomic mobile robot is proposed by integrating a backstepping technique and a neurodynamics model. The tracking control algorithm is derived...
This paper studies the localization of a mobile robot based on neural network based extended Kalman filter (NNEKF) algorithm. Extended Kalman filter (EKF) is used to fuse the information acquired from both the robot optical encoders and ultrasonic sensors in order to estimate the current robot position and orientation. Then the error covariance of the EKF is tracked by the covariance matching technique...
In this paper, a fuzzy-inference controller with Accelerate/Brake (A/B) Module is proposed for navigation control of a mobile robot in dynamic environments. This approach includes target seeking, obstacle avoidance, and optimal path planning. By utilizing the fuzzy controller, a mobile robot could approach a target in a dynamic environment autonomously. The A/B Module of the proposed system is to...
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