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

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 conten...

[1]  QianFeng,et al.  Quasi-synchronization of heterogeneous dynamic networks via distributed impulsive control , 2015 .

[2]  Steven X. Ding,et al.  State and Disturbance Estimator for Time-Delay Systems With Application to Fault Estimation and Signal Compensation , 2007, IEEE Transactions on Signal Processing.

[3]  Yvan Petillot,et al.  Underwater vehicle obstacle avoidance and path planning using a multi-beam forward looking sonar , 2001 .

[4]  James Lam,et al.  Quasi-synchronization of heterogeneous dynamic networks via distributed impulsive control: Error estimation, optimization and design , 2015, Autom..

[5]  David M. Lane,et al.  Robust tracking of multiple objects in sector-scan sonar image sequences using optical flow motion estimation , 1998 .

[6]  Steven X. Ding,et al.  Actuator fault robust estimation and fault-tolerant control for a class of nonlinear descriptor systems , 2007, Autom..

[7]  Daqi Zhu,et al.  A multi-AUV cooperative hunting method in 3-D underwater environment with obstacle , 2016, Eng. Appl. Artif. Intell..

[8]  D. Lane,et al.  Subsea vehicle path planning using nonlinear programming and constructive solid geometry , 1997 .

[9]  Daqi Zhu,et al.  Trajectory Tracking and Re-planning with Model Predictive Control of Autonomous Underwater Vehicles , 2019 .

[10]  Chao Xu,et al.  Object representation for multi-beam sonar image using local higher-order statistics , 2017, EURASIP J. Adv. Signal Process..

[11]  Mike J. Chantler,et al.  Automatic interpretation of sonar image sequences using temporal feature measures , 1997 .

[12]  Vincent Creuze,et al.  Trajectory tracking for autonomous underwater vehicle: An adaptive approach , 2019, Ocean Engineering.

[13]  David P. Williams.  Bayesian Data Fusion of Multiview Synthetic Aperture Sonar Imagery for Seabed Classification , 2009, IEEE Transactions on Image Processing.

[14]  Santosha K. Dwivedy,et al.  Advancements in the field of autonomous underwater vehicle , 2019, Ocean Engineering.

[15]  Simon X. Yang,et al.  Multi-AUV Hunting Algorithm Based on Bio-inspired Neural Network in Unknown Environments , 2015 .

[16]  Daniel W. C. Ho,et al.  A Unified Approach to Practical Consensus with Quantized Data and Time Delay , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[17]  Roger Skjetne,et al.  A Multibeam-Based SLAM Algorithm for Iceberg Mapping Using AUVs , 2018, IEEE Access.

[18]  Jesse Pentzer,et al.  Side scan sonar based self-localization for small Autonomous Underwater Vehicles , 2018, Ocean Engineering.

[19]  Daniel W. C. Ho,et al.  Consensus control for multiple AUVs under imperfect information caused by communication faults , 2016, Inf. Sci..

[20]  Jun Zhao,et al.  Cooperative Adaptive Fuzzy Tracking Control for Networked Unknown Nonlinear Multiagent Systems With Time-Varying Actuator Faults , 2014, IEEE Transactions on Fuzzy Systems.

[21]  I. Quidu,et al.  Robust Multitarget Tracking in Forward-Looking Sonar Image Sequences Using Navigational Data , 2012, IEEE Journal of Oceanic Engineering.

[22]  Neil Bose,et al.  Adaptive Autonomous Underwater Vehicles: An Assessment of Their Effectiveness for Oceanographic Applications , 2019, IEEE Transactions on Engineering Management.