Trajectory tracking algorithm of autonomous mobile platform for animal husbandry environment information monitoring

In order to achieve all-round monitoring of livestock environment, an autonomous mobile monitoring platform for trajectory tracking was developed. The trajectory tracking control problem of autonomous mobile platform was studied. According to the structure of the platform, the system structure and function of the autonomous mobile platform were introduced, including all kinds of sensors that the platform itself needs to perceive, and the measurement sensors needed for animal environment monitoring. And in the structure based autonomous mobile platform, combined with the autonomous mobile platform of four wheel model characteristics and kinematics principle of the simplified two DOF bicycle model, through the analysis of two degree of freedom model to obtain the kinematics model of the bicycle, so as to obtain the platform of steering wheel angle and moving between speed and wheelbase. According to the position and posture relationship between the current point and the desired point of the platform, the error model and the error differential model were obtained by using the geometric method, and it was proved that the platform would eventually converge to the desired trajectory as long as the platform speed and steering wheel angle were accurately controlled. In addition, according to the characteristics of the nonholonomic constraints of the platform, the choice of the expected point was determined by the arc tangent point method. Based on the platform error differential model, a time-varying state feedback control algorithm based on Lyapunov function and Backstepping was proposed, and the trajectory tracking control rate was obtained to achieve the control of steering wheel angle and speed of autonomous mobile platform. The rate was simulated on the platform of Matla2015a software, using the obtained control. The simulation results show that when the initial error is large, the rate control algorithm can make the platform converge to the desired trajectory, the error over time tends to zero. When choosing the platform the maximum speed (vmax,γmax)=(0.18 m/s,0.49 rad), maximum acceleration =(0.25 m/s2,0.5 rad/s), the tracking stability, in the control parameters (k1, k2, k3, k4)=(0.1,0.2,0.15,0.3), linear tracking error is xe=±7 mm, ye=±9.8 mm, θe=±4.2°, arc trajectory tracking error is xe=±6.2 mm, ye =±8.3 mm, θe=±5.8°. The results show that the proposed platform trajectory tracking algorithm can make the convergence of the autonomous mobile platform better on the desired trajectory, and achieved good control accuracy and stability of tracking. The study provides a reference for the overall monitoring of the track tracking control of the autonomous mobile platform in the animal environment.