Hexapod robots are characterized by their static stability, broad application range, and ability to operate in complex environments. To leverage these characteristics and handle various challenging conditions, it is essential to maintain motion stability while enhancing flexibility and safety. This can be achieved either by exerting external flexible control over the robot’s motion or by enabling the robot to adaptively adjust to unknown ground conditions. This paper proposes a gait adaptive control method for hexapod robots based on environmental information. By using the motion velocity and angular velocity of the robot, the target position for the robot’s foot trajectory is calculated. The foot trajectory is then planned using polynomial functions to control and adjust the robot’s overall motion state. Additionally, a fuzzy control method is proposed to convert real-time data collected by the inertial measurement unit into gait control coefficients: the body height coefficient ( K h ), stride distance coefficient ( K I ), and leg lift height coefficient ( K f ). This approach relies solely on the inertial measurement unit, resulting in low cost and hardware requirements. The effectiveness of our control method is verified through experiments on sandy terrain. The results demonstrate that the hexapod robot using the proposed method exhibits improved motion stability compared to nonadaptive gait control. The gait adaptive control method based on environmental information offers an innovative solution for the adaptive motion of multilegged robots in complex environments.
Chen et al. (Fri,) studied this question.