Analysis and Control for an Omnidirectional Mobile Manipulator
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
Robust neuro-fuzzy sensor-based motion control among dynamic obstacles for robot manipulators
IEEE Transactions on Fuzzy Systems
Mobile Manipulators' Object Recognition Method Based on Multi-sensor Information Fusion
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Expert Systems with Applications: An International Journal
Enhanced fuzzy sliding mode controller for robotic manipulators
International Journal of Robotics and Automation
MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators
Information Sciences: an International Journal
A multi-viewpoint system to support abductive reasoning
Information Sciences: an International Journal
Fuzzy embedded mobile robot systems design through the evolutionary PSO learning algorithm
WSEAS TRANSACTIONS on SYSTEMS
Human tracking from a mobile agent: Optical flow and Kalman filter arbitration
Image Communication
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The work presented in this paper deals with the problem of autonomous and intelligent navigation of mobile manipulator, where the unavailability of a complete mathematical model of robot systems and uncertainties of sensor data make the used of approximate reasoning to the design of autonomous motion control very attractive. A modular fuzzy navigation method in changing and dynamic unstructured environments has been developed. For a manipulator arm, we apply the robust adaptive fuzzy reactive motion planning developed in [J.B. Mbede, X. Huang, M. Wang, Robust neuro-fuzzy sensor-based motion control among dynamic obstacles for robot manipulators, IEEE Transactions on Fuzzy Systems 11 (2) (2003) 249-261]. But for the vehicle platform, we combine the advantages of probabilistic roadmap as global planner and fuzzy reactive based on idea of elastic band. This fuzzy local planner based on a computational efficient processing scheme maintains a permanent flexible path between two nodes in network generated by a probabilistic roadmap approach. In order to consider the compatibility of stabilization, mobilization and manipulation, we add the input of system stability in vehicle fuzzy navigation so that the mobile manipulator can avoid stably unknown and/or dynamic obstacles. The purpose of an integration of robust controller and modified Elman neural network (MENN) is to deal with uncertainties, which can be translated in the output membership functions of fuzzy systems.