Multi-autonomous underwater vehicles collaboratively search for intelligent targets in an unknown environment in the presence of interception

Abstract

We present a bionic neural wave network that uses multiple autonomous underwater vehicles to search and acquire intelligent targets in an unknown underwater environment. The neuron pheromone content is arranged according to neural wave diffusion and layer-by-layer energy attenuation, when underwater mesh space based on neural wave diffusion theory was established that the neuron nodes in the neural network structure correspond to obstacles, autonomous underwater vehicles, and targets in the environment. In order to solve the problems of over-allocation and under-allocation of the multi-autonomous underwater vehicles system during the cooperative capture of targets, a redistribution mechanism based on the improved self-organizing map algorithm is implemented and directed to rationalize task distribution. Two different taboo search methods are employed to update the autonomous underwater vehicle path in real time, and the polynomial coefficient solution method is used to fit partial path data. So that the autonomous underwater vehicle trajectory can be obtained and an interceptor position coordinate can be predicted. An auxiliary autonomous underwater vehicle is aimed to replace the intercepted autonomous underwater vehicle and the matching capture points are tracked to ensure the completion of the task so that the full range of hunting targets is identified. In order to simulate an unknown complex underwater environment, obstacles are randomly arranged around the target, the location information of the obstacle, and the target is unknown and unpredictable. Four simulation experiments were performed to verify the accuracy and efficiency of the algorithm under unknown environment. The results show that this algorithm can improve the path update average efficiency by 66% compared with other algorithms. Obviously, this algorithm is reasonable and effective.

Research on Scheme Design and Decision of Multiple Unmanned Aerial Vehicle Cooperation Anti-Submarine Based on Knowledge-Driven Soft Actor-Critic

“…In paper [18], the Clausius bio-inspired neural network and bio-inspired cascaded tracking control approach have been implemented for the search and obstacle avoidance tasks of the UAV. A bionic neural wave network was presented in paper [19], which built a neural node structure based on the theory of neural wave diffusion. In this structure, neurons correspond to the obstacles, agents, and the searched targets in the environment.…”

Modeling and analysis of information automation in intelligent substation auxiliary monitoring system

“…Since the 21st century, the development of science and technology is changing with each passing day, and digital technology has become the frontier technology in the world today [1]. With the continuous development of intelligent electricity in China, especially the appearance of electromechanical integration devices such as electronic transformers and intelligent switches, the development and utilization of modern computer high-speed network technology in real-time systems, and the growing maturity of substation operation training and simulation technologies, substations have entered a new stage of digitalization [2]. At present, many auxiliary subsystems of substation, such as video monitoring, environmental monitoring, security, fire alarm, access control, etc., mostly operate independently, uploading data through different channels, and even each system is equipped with independent management personnel.…”