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A neural network based controller is derived for a mobile manipulator to track the given trajectories in the workspace. The dynamics of the mobile manipulator is assumed to be unknown completely, and is learned on-line by the radial basis function network (RBFN) with weight adaptation rule derived from the Lyapunov function. Generally, a RBFN can be used to(More)
This paper proposes an adaptive robust control scheme for free-flying space robots. In order to simply and effectively control free-flying space robots subject to parameter uncertainty and disturbances, to avoid the measurement of the base(space vehicle) acceleration , and t o eliminate the assumption that the uncertainty bounds must be a priori known in(More)
This paper describes a dynamical local path-planning algorithm of a n autonomous mobile robot available for stationary obstacle avoidance using non-linear friction. Dynamical path-planning algorithm is considered to accommodate the mobile robot to the dynamic situation of the path-planning nature. Together with the previous virtual force field (VFF) method,(More)