Stability Enhancement of Mobile Manipulators via Soft Computing

Nowadays the size and dimension of mobile manipulators have been decreased for being usable in various regions. This leads several problems such as danger of instability. Therefore, many researches have been done to overcome the problem of overturning of a mobile manipulator. In this paper, an algorithm for increasing the stability of a mobile manipulator is presented based on the optimization of a performance index. The path of vehicle and the desired task of the end-effector are predefined. In order to apply the optimal stability criterion, it is more convenient that the manipulator be of a redundant. Considering the interaction between the vehicle and the manipulator and using the genetic algorithm to minimize the stability criterion cooperating with a neural network, the proposed method is a swift algorithm to determine the optimum configuration of the manipulator for real time overturning control of the vehicle. An example for illustrating the significance of the proposed method is presented in a two dimensional configuration.