Robust Optimization of Routing Robot for Prediction, Estimation and Target Trajectory based on Bat Algorithm

Mobile robots have a wide range of applications in the industry. It is necessary and necessary to determine its errors in parametric and non-parametric indeterminate conditions, as well as to provide a robust controller along with tracking the target in them. Hence, the research has been attempting to provide a controller-based target tracking method for estimating control errors in mobile robots. The proposed method is to use the LQR controller as robust and optimized and use the Bat Algorithm node's observation to calculate and identify control errors. A linear Kalman filter is also used to track targets in a moving robot. The results show that the proposed method has a good performance compared to previous methodsMobile robots have a wide range of applications in the industry. It is necessary and necessary to determine its errors in parametric and non-parametric indeterminate conditions, as well as to provide a robust controller along with tracking the target in them. Hence, the research has been attempting to provide a controller-based target tracking method for estimating control errors in mobile robots. The proposed method is to use the LQR controller as robust and optimized and use the Bat Algorithm node's observation to calculate and identify control errors. A linear Kalman filter is also used to track targets in a moving robot. The results show that the proposed method has a good performance compared to previous methods