Mobile manipulators are developed in order to execute separately in various regions where there is not possibility for human to appear there. Recently, the size of mobile manipulators has been decreased according to their given tasks. For such systems, the stability issue is very important. The robot system should be able to keep itself in an optimal situation. For reaching to this goal, one can use a redundant degree of freedom for the mobile manipulator such that this redundancy makes it possible to recover the system's stability by dynamic compensatory motion of manipulator when the system is unstable. In this paper, we present an algorithm which is fast enough to stabilize the mobile manipulator with the best stability criterion based on a neural network and genetic algorithm which cooperate together. For applying the optimal values as the algorithm outputs to the appropriate joints, a PD controller is used. The significance of this algorithm is provided for a spatial mobile manipulator with a predefined trajectory of the end-effector and the vehicle.

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