The adaptive motion control method for bio-inspired hexapod robot is explored based on bionics principles,as well as the limb structure and behavioral characteristics of tarantulas.Firstly,a bionic kinematic model for a single leg of the robot is established using the Denavit-Hartenberg method combined with mechanical parameters.The forward and inverse kinematic expressions are derived,and the triangular gait of the hexapod robot is implemented through composite cycloid trajectory planning.Subsequently,inspired by biological tactile sense and biological vestibular balance mechanisms,force sensors and inertial measurement unit are employed to acquire force control and posture information of the hexapod robot,followed by fusion processing,which enables the robot to perceive environmental changes and adjust its trajectory in real time.A motion control model integrating hybrid gaits is proposed to enhance the robot's environmental perception and adaptability.Finally,a semi-physical simulation experimental platform is constructed to verify the effectiveness and reliability of the proposed model.Experimental results demonstrate that this model can significantly improve the motion stability and traversal efficiency of the robot in complex and rugged terrains,providing robust support for the application of bio-inspired adaptive control methods in multi-legged robots.

The adaptive motion control method for bio-inspired hexapod robot is explored based on bionics principles,as well as the limb structure and behavioral characteristics of tarantulas.Firstly,a bionic kinematic model for a single leg of the robot is established using the Denavit-Hartenberg method combined with mechanical parameters.The forward and inverse kinematic expressions are derived,and the triangular gait of the hexapod robot is implemented through composite cycloid trajectory planning.Subsequently,inspired by biological tactile sense and biological vestibular balance mechanisms,force sensors and inertial measurement unit are employed to acquire force control and posture information of the hexapod robot,followed by fusion processing,which enables the robot to perceive environmental changes and adjust its trajectory in real time.A motion control model integrating hybrid gaits is proposed to enhance the robot's environmental perception and adaptability.Finally,a semi-physical simulation experimental platform is constructed to verify the effectiveness and reliability of the proposed model.Experimental results demonstrate that this model can significantly improve the motion stability and traversal efficiency of the robot in complex and rugged terrains,providing robust support for the application of bio-inspired adaptive control methods in multi-legged robots.