Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Harmonic functions as a basis for motor control and planning
Harmonic functions as a basis for motor control and planning
Fuzzy navigation for robotic manipulators
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Robust Tracking Control of Robot Manipulators
Robust Tracking Control of Robot Manipulators
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Neurofuzzy Motion Planners for Intelligent Robots
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
Back-driving a truck with suboptimal distance trajectories: a fuzzy logic control approach
IEEE Transactions on Fuzzy Systems
Human tracking from a mobile agent: Optical flow and Kalman filter arbitration
Image Communication
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An integration of fuzzy controller and modified Elman neural networks (NN) approximation-based computed-torque controller is proposed for motion control of autonomous manipulators in dynamic and partially known environments containing moving obstacles. The fuzzy controller is based on artificial potential fields using analytic harmonic functions, a navigation technique common used in robot control. The NN controller can deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamics of the robot arm. The NN weights are tuned on-line, with no off-line learning phase required. The stability of the closed-loop system is guaranteed by the Lyapunov theory. The purpose of the controller, which is designed as a neuro-fuzzy controller, is to generate the commands for the servo-systems of the robot so it may choose its way to its goal autonomously, while reacting in real-time to unexpected events. The proposed scheme has been successfully tested. The controller also demonstrates remarkable performance in adaptation to changes in manipulator dynamics. Sensor-based motion control is an essential feature for dealing with model uncertainties and unexpected obstacles in real-time world systems.