Working Path Optimization of AUV Manipulator Based on PSO-GA Algorithm

The work path optimization of AUV manipulator based on PSO GA algorithm is a method to find the best work path of AUV manipulator. It is an extension of the original PSO GA algorithm, and uses the concept of pseudo Gaussian distribution to find a better solution under multiple local optimizations. The working path optimization of the underwater robot manipulator is to make the control of the underwater robot manipulator move along the working path with the minimum energy consumption. It is realized by using some mathematical techniques and algorithms. The main idea behind this technology is to find out the best point of the mobile underwater robot manipulator to minimize its total energy consumption. This technology is used for many purposes, such as motion planning, path planning and control design.. The main idea behind this algorithm is that if there are multiple local optima, the global optimal can be found by minimizing the total cost function of all local optima. This can be achieved by using Lagrange multiplication (LMM). In addition, this technology requires less computing power. In the actual working environment and experimental environment, the magnetic field interference may have an impact on the attitude parameters of AUV, which leads to the unsatisfactory control effect of AUV motion. In order to accurately measure the attitude of AUV system, this paper proposes an anti-jamming and fault-tolerant processing algorithm for MEMS inertial navigation system. This algorithm first estimates the signal residual, then dynamically adjusts the confidence level of local filter through the residual value, and finally fuses sensor signals with different working principles through the confidence level, which can significantly improve the stability and reliability of attitude feedback signals.