# Research on the Posture Control Method of Hexapod Robot for Rugged Terrain
## 6 Conclusions  
This paper proposed a rugged terrain adaptive strategy based on foot trajectory to solve the problem of hexapod robot posture control in the unstructured terrain climbing. The unstructured terrain was judged as mild unstructured and severe unstructured, and the corresponding posture adjustment mode was activated by combining the change of foot trajectory and the autonomous terrain judgment strategy based on LIT. A VSDM was established to keep the trunk moving smoothly based on the initial posture and reduce the influence of mild unstructured terrain on posture changes. In severe unstructured terrain, the hexapod robot actively adjusts the height and inclination of the trunk and uses the main support triangle MP formed by the support foot as the reference plane for posture adjustment. According to the MP projection in the MATLAB simulation experiment, when the robot passes through rugged ground, the variation curve of trunk yaw angle, pitch angle, and roll angle will either maintain a zero value or change smoothly and slowly at different stages, and the robot can switch between mild and severe unstructured posture control mode in a timely manner. The experiments show that the posture controller based on the VSDM model can filter out the disturbance of external environment and unstable factors of the robot's own motion. In addition, the robot can autonomously identify the changing stair terrain and adopt the corresponding posture control strategy to make it successfully complete the stair climbing. The innovation of the posture adjustment strategy for uneven terrain in this paper is as follows: First, the hexapod robot can automatically divide the climbing terrain into mild uneven terrain and severe uneven terrain according to the foot motion trajectory, and accurately activate the corresponding posture adjustment strategy according to the terrain. Second, the hexapod robot adjusts its posture according to the VSDM model for flat and mild uneven terrain. In severe uneven terrain, the robot needs to adjust one of the trunk's height, pitch angle, and deflection angle based on the main support triangle MP. Under the premise of ensuring the robot's climbing ability, the hybrid use of the two posture adjustment strategies improves the passing efficiency. Third, the simulation and experimental results show that the control method can switch the posture control mode in a timely manner. The posture controller based on the VSDM model can filter out the external environment disturbance and unstable factors of the robot's own motion and improve the stability of the motion on the basis of realizing the target motion. This control method has good adaptability and passing performance to unstructured terrain. The experimental results showed that the VSDM controller can filter out small vibrations during the adjustment of the pose, but the smoothness of the adjustment needs to be further enhanced. When the robot travels heavy rugged terrain, the degree of torso vibration was more than when traversing lightly rugged terrain. The posture adjustment control algorithm and controller used in the heavy rugged walking need to be optimized. In view of the above problems, the hexapod robot needs to be studied in depth from the following aspects: First, the hexapod robot needs to redesign and optimize the controller to improve the control accuracy, response speed, and stability of the torso during the adjustment process. Second, improve the accuracy and speed of robot attitude adjustment for heavy rugged terrain. Third, more external interference should be added in subsequent experiments to verify the adaptability of the robot in a complex environment. [PERSON] built the dynamic model of the hexapod robot, contributed to the mathematical model, and was responsible for the experiments. [PERSON] contributed to the program design of the pose controller and wrote the paper. [PERSON] developed and came up with ideas about the pose control method for the hexapod robot. [PERSON] oversaw and advised the research.