# Study on Head Stabilization Control Strategy of Non-Wheeled Snake Robot Based on Inertial Sensor
## 1 Introduction  
A snake robot has a relatively unique movement mode, and it moves with the friction force between itself and the ground as power. Due to its high degree of freedom (DOF), snake robots have high flexibility. Equipped with cameras, sensors and other equipment, snake robots can complete corresponding tasks on various complex terrains [1]. Snake robots can carry out search and rescue work in the ruins of a disaster area [2]; they can perform search work in narrow spaces [3]; they can complete a fire-fighting task at a dangerous fire scene [4]; due to the slender external structure of snake robots [5], they can complete an exploration operation underground or in a pipeline [6]; they can replace humans in an environment full of poisonous gas and other dangerous areas to complete investigations; they can complete tasks such as investigation, assassination and blasting on dangerous battlefields due to their relatively concealed movements; and in the direction of aerospace, they can replace ordinary robots to complete tasks such as detection and sampling, and other tasks in complex and unknown environments, and can also perform maintenance on a space station. In addition, snake robots can be used in the medical field [7]. Since snake robots are slender overall, their control method in the elastic variable channel can be used to promote the multi-directional development of medical endoscopes. Due to the various advantages of snake robots, they are full of research value. Snake robots with visual sensors such as cameras or lidars can detect and navigate in some unknown environments [8]. However, due to the movement characteristics of the snake robot, its head bobs when it is moving, which causes the head vision sensor to fail to obtain external visual information normally and affects the robot's navigation. Therefore, the study of the head stabilization of snake robots in planar motion is an important research topic. Carnegie Mellon University used the mode decomposition method to keep the head of the snake robot in the same direction during the rolling gait [9]. This method can ensure that the head camera of the snake robot works normally during the rolling gait. [PERSON] et al. stabilized the head of the snake robot by controlling the motion of its neck [10]. However, when the method is converted from a continuous model to a discrete model, it causes the head position to move forward and backward, and the control of the robot is impacted. [PERSON] compensated for the head offset angle of the snake robot by calculating the derivative of the snake curve with respect to time [11]. [PERSON] et al. introduced a virtual joint as the desired direction and analyzed the joint angle relationship between the virtual joint and the first two joints of the head in HNC (head navigation control) [12]. However, this lacks validation on the effect of head navigation, and it is difficult to tune parameters using a cyclic inhibition model. [PERSON] et al. achieved partial control and proposed to divide the snake robot into different parts such as the head, neck and torso. The torso is used to push the snake robot forward, while the neck and head are used to control the snake robot's direction [13]. However, this method needs to treat multiple modules as the neck part, so the number of joints increases, which is difficult to apply to the CPG model based on curvature control. [PERSON] et al. described the direction of motion with a virtual coordinate system model, and studied HNC using the Kuramoto oscillator model based on a single-chain bidirectional coupling network [14]. Based on a CPG network [15], [PERSON] et al. used virtual joints to stabilize the head. Although this solution can effectively ensure the head stabilization of a snake robot [16], it lacks the feedback of head position information, and the efficiency is not high. The authors of [17] used the main ailerons and the tail elevators to counteract the pitch angle.