Research on Navigation for Search and Rescue Robot Based on Traversability
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Adaptive Neuro-fuzzy Network Control for a Mobile Robot
Journal of Intelligent and Robotic Systems
Wheelchairs Embedded Control System Design for Secure Navigation with RF Signal Triangulation
Journal of Information Technology Research
The bio-inspired model based hybrid sliding-mode tracking control for unmanned underwater vehicles
Engineering Applications of Artificial Intelligence
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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One important problem in autonomous robot navigation is the effective following of an unknown path traced in the environment in compliance with the kinematic limits of the vehicle, i.e., bounded linear and angular velocities and accelerations. In this case, the motion planning must be implemented in real-time and must be robust with respect to the geometric characteristics of the unknown path, namely curvature and sharpness. To achieve good tracking capability, this paper proposes a path following approach based on a fuzzy-logic set of rules which emulates the human driving behavior. The input to the fuzzy system is represented by approximate information concerning the next bend ahead the vehicle; the corresponding output is the cruise velocity that the vehicle needs to attain in order to safely drive on the path. To validate the proposed algorithm two completely different experiments have been run: in the first experiment, the vehicle has to perform a lane-following task acquiring lane information in real-time using an onboard camera; in the second, the motion of the vehicle is obtained assigning in real-time a given time law. The obtained results show the effectiveness of the proposed method