Cooperative Navigation Based on Cross Entropy: Dual Leaders

Abstract

Cooperative navigation aims at improving positioning accuracy of Autonomous Underwater Vehicles (AUVs). In this paper, a dual leaders cooperative navigation method is proposed based on Cross Entropy (CE) algorithm. Since the trajectories of the slave AUVs are assumed to be predetermined, the Markov Decision Process (MDP) is also integrated in the proposed algorithm to generate optimal trajectories of master AUVs from the perspective of probability. Firstly, the navigation model and cost functions are established for the cooperative navigation system with multiple masters and slaves. Then, the CE algorithm is used to train the system with help of MDP to obtain the path of the master AUVs. In the simulation, the cooperative localization trajectories of the slave AUVs are obtained by Extended Kalman Filter (EKF) and are compared with other positioning methods. The results show that the trajectories of dual master AUVs obtained by the proposed algorithm can not only reduce the observation error of the slave AUVs in the system effectively, but also keep relative measurement distance between the master AUVs and the slave AUVs in a suitable range. INDEX TERMS Cooperative navigation, cross entropy, Markov decision process, path planning.

Optimal Formation Configuration Analysis for Cooperative Localization System of Multi-AUV

“…According to equation ( 22), the optimal formation configuration for the cooperative localization system of multi-AUV is a constant value different from the performance evaluation function value of the special formation configuration proposed in this paper, which is independent of the number of master AUVs in the multi-AUV system, and this constant value is small. To further discuss the difference of cooperative localization performance between the optimal formation configuration and the special formation configuration, this paper takes m ∈ [4,20], and uses the numerical analysis method to discuss the influence of this constant value on the performance evaluation function value of the optimal formation configuration. As shown in Fig.…”

“…At present, the research of cooperative localization technology based on distance measurement mainly focuses on improving the positioning accuracy of AUV through algorithms. Based on the assumption that the navigation trajectory of the slave AUV is known, Zhang [4] combined with the Markov Decision Process to analyze the optimal trajectory of the master AUV from the perspective of probability and proposed the cooperative navigation algorithm based on crossentropy: dual leaders. To tackle at the problem of heavy-tailed measurement noise caused by non-Gaussian measurement in the cooperative localization system of AUV, Sun [5] combined with the advantages of DDF and the maximum correlation entropy criterion, and proposed a maximum entropy divided difference filter for cooperative localization.…”

Multi-AUV Cooperative Navigation Algorithm Based on Temporal Difference Method

“…Gao et al [16] proposed a cooperative multi-AUV localization algorithm based on a distributed extended information filter (DEIF) to solve the cooperation problem in decentralized architectures. This approach only requires smaller data transmission packets to effectively solve the communication constrained problem underwater.…”

Multi-UUV Cooperative Dynamic Maneuver Decision-Making Algorithm Using Intuitionistic Fuzzy Game Theory

“…e multi-UUV control algorithm has gained increased attention, which involves a multi-UUV cooperative formation control, cooperative navigation, cooperative confrontation, etc. [1][2][3][4][5]. At present, research on multi-UUV collaborative formation and navigation has had prosperous developments [2,6].…”

“…[1][2][3][4][5]. At present, research on multi-UUV collaborative formation and navigation has had prosperous developments [2,6]. However, studies on multi-UUV cooperative confrontation are still quite limited.…”