Combined Use of Ground Learning Model and Active Compliance to the Motion Control of Walking Robotic Legs

Position control alone is not sufficient for practical motion control of a legged robot when it walks on softuneven terrain or in an unknown environment. In order to improve terrain adaptability of walking robots, foot force control is needed. In this article, a foot force/position adjustment method, the hybrid Ground-Learning model and Active Compliance force control method (in short, the hybrid GLAC method) is introduced. The proposed method combines active compliance force control with a groundlearning model to control of leg motion of the robot. The ground model here reflects the relationship between the leg-end force and the sinkage. To verify the control quality of the proposed method, together with Active Compliance control (AC control) and Ground Learning model control (GL control), experiments based on a robotic leg have been carried out on hard and soft terrain, respectively. The results show that the proposed method can ensure the actual leg-end force to follow closely the changing of reference forces both on hard and soft terrain. Therefore, by using hybrid GLAC control, the error of the actual forces relative to the reference forces can be reduced more quickly than by using AC method.