Abstract
For a target search of autonomous underwater vehicles (AUVs) in a completely unknown three-dimensional (3D) underwater environment, a multi-AUV collaborative target search algorithm based on adaptive prediction is proposed in this paper. The environmental information sensed by the forward-looking sonar is used to judge the current state of view, and the AUV system uses this environmental information to perform the target search task. If there is no target in the field of view, the AUV system will judge whether all sub-regions of the current layer have been searched or not. The next sub-region for searching is determined by the evaluation function and the task assignment strategy. If there are targets in the field of view, the evaluation function and the estimation function of the adaptive predictive optimization algorithm is used to estimate the location of the unknown target. At the same time, the algorithm also can reduce the positioning error caused by the noise of the sonar sensor. In this paper, the simulation results show that the proposed algorithm can not only deal with static targets and random dynamic interference target search tasks, but it can also perform target search tasks under some random AUV failure conditions. In this process, the underwater communication limits are also considered. Finally, simulation experiments indicate the high efficiency and great adaptability of the proposed algorithm.
Highlights
In modern marine military, underwater environment reconnaissance is achieved mainly by autonomous underwater vehicles (AUVs)
In order to effectively conduct a searching task in complex underwater condition, it is important to analyze the factors that may affect cooperative searching for multi-AUVs: 1. Communication restrictions: Since the AUV cannot receive GPS (Global Positioning System) signals when it operates in an underwater environment, the AUV can only rely on the inertial measurement unit and the Doppler log in the target search process, as well as the filters to navigate
This paper presents an adaptive prediction algorithm for cooperative target search tasks of multi-AUV
Summary
Underwater environment reconnaissance is achieved mainly by autonomous underwater vehicles (AUVs). References [31,32,33] aims at multi-robots in a dynamic environment to collaboratively select multiple targets in a dynamic environment, and uses a computer simulation of dynamic environment changes to achieve multi-target selection of multi-robot motion behavior coordination Such a method, along with multi-robot communication and multi-task coordination strategies, allowed for high-efficiency AUV work in target searching and tracking in complicated environments, whereas the method was only suitable in two-dimensional situations. For a three-dimensional unknown underwater environment, the target search methods in above-mentioned literature are only beneficial for improving the efficiency of target searching and the optimization performance in either global known environment or locally known environment These methods could not be directly used to solve the problem of collaborative target search for multiple.
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