Gait and trajectory rolling planning for hexapod robot in complex environment

Abstract

Hexapod robots have stronger adaptability to dynamic unknown environment than wheeled or trucked ones due to their flexibility. In this paper, a control strategy based on rolling gait and trajectory planning that enables a hexapod robot to walk in dynamic environment is proposed. The core content of the control strategy is to constantly change the gait and trajectory according to the dynamic environment and predicted stability margin of robot. Kalman filter is employed to compute predicted zero moment point (ZMP) monitoring the stability of robot in order to keep balance with adjusting gait and trajectory. A hierarchical control architecture consisting of high-level gait planner, low-level trajectory planner, joint servo controller and compliance controller is presented. The control strategy is applied to a hexapod robot engaging to disaster rescue. Experiment results show the efficiency of our control strategy over challenging terrain.