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Stability and performance are two main issues in motion of bipeds. To ensure stability, motion of a biped needs to follow specific pattern to comply with certain stability criterion such as zero moment point. Actuator torques limitation is also a serious restriction on motion path. Indeed, the velocity of the robot during each step is bounded with robot's physical limitations. The motion path of the robot is designed considering environmental conditions and robot's tasks. Therefore, online trajectory planning is one of the most important problems in this field. In this paper a neural network based algorithm for stable path generation is introduced which can be used online to generate path for a biped carrying different payloads. The neural network is trained based on optimum paths generated by a genetic algorithm for different values of payload mass, while considering actuator limits as optimization constraints.