Automatica (Journal of IFAC)
Engineering Applications of Artificial Intelligence
Robust adaptive control of cooperating mobile manipulators with relative motion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A control of two wheels driven redundant mobile manipulator using a monocular camera system
International Journal of Intelligent Systems Technologies and Applications
Neuro-fuzzy network control for a mobile robot
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International Journal of Applied Mathematics and Computer Science - Special Section: Robot Control Theory Cezary Zielinski
Adaptive dynamic coupling control of human-symbiotic wheeled mobile manipulators with hybrid joints
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Journal of Intelligent and Robotic Systems
ICIRA'10 Proceedings of the Third international conference on Intelligent robotics and applications - Volume Part I
Adaptive Neuro-fuzzy Network Control for a Mobile Robot
Journal of Intelligent and Robotic Systems
Information Sciences: an International Journal
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Design and development of a wearable rehabilitation robot
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Posture Stabilization Strategy for a Trotting Point-foot Quadruped Robot
Journal of Intelligent and Robotic Systems
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In this paper, adaptive robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The proposed control is robust not only to parameter uncertainties such as mass variations but also to external ones such as disturbances. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance and the bounded constraint force. Simulation results validate that the motion of the system converges to the desired trajectory, and the constraint force converges to the desired force