Formation Control of Multiple Unmanned Surface Vehicles Using the Adaptive Null-Space-Based Behavioral Method

This paper presents an adaptive null-space-based behavioral (NSB) method to deal with the problems of saturation planning and lack of adaptability when the traditional NSB method is applied to the formation control of multiple unmanned surface vehicles (MUSVs). First, the NSB method is analyzed, and the matrix theory is introduced to propose a behavior priority theory determination method based on a vector graph. Second, consider the maneuverability of the unmanned surface vehicle (USV), variable coefficients with physical significances are introduced to redefine the behavioral motion model, making the speed limit solved in each working condition within the maneuvering range of the USV and effectively improving the formation ability of MUSVs. Third, a logical priority collision avoidance strategy between the MUSVs is proposed, aiming at the problem that when the USVs judge each other as obstacles, both of them adopt the obstacle avoidance behavior resulting in two vehicles’ courses deviating from the direction of the target point. Finally, a simulation platform for the formation control of MUSVs was established by taking the Dolphin-I prototype USV as the experimental object, and the feasibility of the proposed method was verified by a simulation test.

[1]  Nikola Miskovic,et al.  Fast in‐field identification of unmanned marine vehicles , 2011, J. Field Robotics.

[2]  Zhong Wang,et al.  Dynamic Output Feedback Guaranteed-Cost Synchronization for Multiagent Networks With Given Cost Budgets , 2018, IEEE Access.

[3]  Andrea Gasparri,et al.  Swarm-based path-following for cooperative unmanned surface vehicles , 2014 .

[4]  Li Guo-zhong Structure of the Generalized Zero Space of Matrix , 2007 .

[5]  Cheng Wang,et al.  Completely Distributed Guaranteed-Performance Consensualization for High-Order Multiagent Systems With Switching Topologies , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[6]  Ye Li,et al.  Heading control method and experiments for an unmanned wave glider , 2017 .

[7]  Zheng Zhi-qiang A Null-Space-Based Control Method for Soccer Robots , 2011 .

[8]  Guoqing Zhang,et al.  Novel DVS guidance and path-following control for underactuated ships in presence of multiple static and moving obstacles , 2018, Ocean Engineering.

[9]  Ye Li,et al.  Layered berthing method and experiment of unmanned surface vehicle based on multiple constraints analysis , 2019, Applied Ocean Research.

[10]  Thor I. Fossen,et al.  Formation Control of Underactuated Surface Vessels using the Null-Space-Based Behavioral Control , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Gianluca Antonelli,et al.  Decentralized centroid and formation control for multi-robot systems , 2013, 2013 IEEE International Conference on Robotics and Automation.

[12]  Jawhar Ghommam,et al.  Coordinated Path-Following Control for a Group of Underactuated Surface Vessels , 2009, IEEE Transactions on Industrial Electronics.

[13]  Craig A. Woolsey,et al.  Modeling, Identification, and Control of an Unmanned Surface Vehicle , 2013, J. Field Robotics.

[14]  António Manuel Santos Pascoal,et al.  Adaptive leader-follower formation control of autonomous marine vehicles , 2014, 53rd IEEE Conference on Decision and Control.

[15]  Lei Wan,et al.  Serret-Frenet frame based on path following control for underactuated unmanned surface vehicles with dynamic uncertainties , 2015 .

[16]  Satyandra K. Gupta,et al.  Resolution-adaptive risk-aware trajectory planning for surface vehicles operating in congested civilian traffic , 2016, Auton. Robots.

[17]  Hai Lin,et al.  Platoon Formation Control With Prescribed Performance Guarantees for USVs , 2018, IEEE Transactions on Industrial Electronics.

[18]  Yulei Liao,et al.  Redefined Output Model-Free Adaptive Control Method and Unmanned Surface Vehicle Heading Control , 2020, IEEE Journal of Oceanic Engineering.

[19]  Mingjun Zhang,et al.  Trajectory tracking control for underactuated unmanned surface vehicles with dynamic uncertainties , 2016 .

[20]  Jie Huang,et al.  Distributed tracking for networked Euler-Lagrange systems without velocity measurements , 2014 .

[21]  Ye Li,et al.  Heading MFA control for unmanned surface vehicle with angular velocity guidance , 2018 .

[22]  Xianku Zhang,et al.  Practical constrained dynamic positioning control for uncertain ship through the minimal learning parameter technique , 2018, IET Control Theory & Applications.

[23]  Xiang Li,et al.  A New Decentralized Planning Strategy for Flocking of Swarm Robots , 2010, J. Comput..

[24]  Thor I. Fossen,et al.  Formation Control of Marine Surface Vessels Using the Null-Space-Based Behavioral Control , 2006 .

[25]  Tieshan Li,et al.  Leaderless and leader-follower cooperative control of multiple marine surface vehicles with unknown dynamics , 2013 .

[26]  Les Elkins,et al.  The Autonomous Maritime Navigation (AMN) project: Field tests, autonomous and cooperative behaviors, data fusion, sensors, and vehicles , 2010, J. Field Robotics.

[27]  Jie Huang,et al.  Formation control of multiple Euler-Lagrange systems via null-space-based behavioral control , 2015, Science China Information Sciences.