Survey of approaches for improving the intelligence of marine Surface Vehicles

Waterborne transport faces challenges such as increasing volume, higher environmental requirements and more serious shortage of seafarers in the future. Intelligent vessels, which means that they can comprehend the surroundings and figure out what to do autonomously, could relieve these challenges. However, currently there are few applications of intelligent vessels for civilization use. On the other hand, a variety of technologies has been applied successfully for military or environmental use vessels. This paper summarizes the general architecture of an intelligent vessel based on the existing Unmanned Surface Vehicles (USVs) and then focuses on the internal algorithmic techniques when representing such a vessel as a hierarchical system, from multi-source data fusion, path planning to low level motion control. Alongside, cooperative vessel formation control is briefly reviewed. Then, translation of the theories, algorithms and applications in these fields to the domain of intelligent transportation vessels is discussed. Possible directions for future research in intelligent transport vessels are outlined.

[1]  J. Curcio,et al.  SCOUT - a low cost autonomous surface platform for research in cooperative autonomy , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[2]  Justin E. Manley Development of the autonomous surface craft "ACES" , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[3]  Paul Newman MOOS - Mission Orientated Operating Suite , 2008 .

[4]  Han-Pang Huang,et al.  Dynamic visibility graph for path planning , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[5]  Hiroyuki Yamato,et al.  H∞ control design to include nonlinearities. Second report: nonlinearities in equations of motion , 2002 .

[6]  Hugh F. Durrant-Whyte,et al.  Inertial navigation systems for mobile robots , 1995, IEEE Trans. Robotics Autom..

[7]  Khac Duc Do,et al.  Global waypoint tracking control of underactuated ships under relaxed assumptions , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[8]  T.I. Fossen,et al.  Nonlinear formation control of marine craft with experimental results , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[9]  Robert Sutton,et al.  The design of a navigation, guidance, and control system for an unmanned surface vehicle for environmental monitoring , 2008 .

[10]  Justin E. Manley,et al.  Evolution of the autonomous surface craft AutoCat , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[11]  Ernst Dieter Gilles,et al.  Track-keeping on waterways using model predictive control , 1998 .

[12]  Zhen Li,et al.  Disturbance Compensating Model Predictive Control With Application to Ship Heading Control , 2012, IEEE Transactions on Control Systems Technology.

[13]  Roger Skjetne,et al.  Nonlinear maneuvering and control of ships , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[14]  Khac Duc Do,et al.  State- and output-feedback robust path-following controllers for underactuated ships using Serret–Frenet frame , 2004 .

[15]  Yan Ming-zhong Survey on technology of mobile robot path planning , 2010 .

[16]  Linda S. Gottfredson,et al.  Foreword to “intelligence and social policy” , 1997 .

[17]  Carlos Silvestre,et al.  The use of “CARAVELA 2000®” vehicles in operational oceanography , 2002 .

[18]  Thor I. Fossen,et al.  Handbook of Marine Craft Hydrodynamics and Motion Control: Fossen/Handbook of Marine Craft Hydrodynamics and Motion Control , 2011 .

[19]  J. Majohr,et al.  Modelling, simulation and control of an autonomous surface marine vehicle for surveying applications Measuring Dolphin MESSIN , 2006 .

[20]  Jing Sun,et al.  Path following for marine surface vessels with rudder and roll constraints: An MPC approach , 2009, 2009 American Control Conference.

[21]  Wendi Heinzelman,et al.  A general data fusion architecture , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[22]  Zhong-Ping Jiang,et al.  Global tracking control of underactuated ships by Lyapunov's direct method , 2002, Autom..

[23]  Carlos Silvestre,et al.  Cooperative control of multiple surface vessels in the presence of ocean currents and parametric model uncertainty , 2010 .

[24]  Narendra Ahuja,et al.  A potential field approach to path planning , 1992, IEEE Trans. Robotics Autom..

[25]  Zhong-Ping Jiang,et al.  Robust adaptive path following of underactuated ships , 2004, Autom..

[26]  Tam'as Vicsek,et al.  Patterns, transitions and the role of leaders in the collective dynamics of a simple robotic flock , 2011 .

[27]  Jr. J.J. LaViola,et al.  A comparison of unscented and extended Kalman filtering for estimating quaternion motion , 2003, Proceedings of the 2003 American Control Conference, 2003..

[28]  Markos Papageorgiou,et al.  The impact of automatic control on recent developments in transportation and vehicle systems , 2005, Annu. Rev. Control..

[29]  Yang Gao,et al.  Comparison and Analysis of Centralized, Decentralized, and Federated Filters , 1993 .

[30]  Rita Cunha,et al.  A PATH-FOLLOWING CONTROLLER FOR THE DELFIMX AUTONOMOUS SURFACE CRAFT , 2006 .

[31]  Zixing Cai,et al.  Cooperative Coevolutionary Adaptive Genetic Algorithm in Path Planning of Cooperative Multi-Mobile Robot Systems , 2002, J. Intell. Robotic Syst..

[32]  Ren C. Luo,et al.  Multisensor fusion and integration: approaches, applications, and future research directions , 2002 .

[33]  N. Mort,et al.  Multi-sensor data fusion architecture based on adaptive Kalman filters and fuzzy logic performance assessment , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[34]  Asgeir J. Sørensen,et al.  An overview of the marine systems simulator (MSS) : a Simulink toolbox for marine control systems , 2006 .

[35]  A. Pascoal,et al.  Vehicle and Mission Control of the DELFIM Autonomous Surface Craft , 2006, 2006 14th Mediterranean Conference on Control and Automation.

[36]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[37]  J Chudley,et al.  A FUZZY LOGIC BASED MULTI-SENSOR NAVIGATION SYSTEM FOR AN UNMANNED SURFACE VEHICLE , 2006 .

[38]  Simon X. Yang,et al.  Genetic algorithm based path planning for a mobile robot , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[39]  Huu-Thanh Nguyen,et al.  An optimal autopilot for ships using a regressive exogenous model , 2004, IEEE International Symposium on Communications and Information Technology, 2004. ISCIT 2004..

[40]  Khac Duc Do,et al.  Robust path-following of underactuated ships : Theory and experiments on a model ship , 2006 .

[41]  Bradley Churcher Differential global positioning system , 2011 .

[42]  Benjamin Kuipers,et al.  Local metrical and global topological maps in the hybrid spatial semantic hierarchy , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[43]  Yang Wang,et al.  Path following control of underactuated ships based on unscented Kalman filter , 2010 .

[44]  Andy Ju An Wang,et al.  Path Planning for Virtual Human Motion Using Improved A* Star Algorithm , 2010, 2010 Seventh International Conference on Information Technology: New Generations.

[45]  H.R. Momeni,et al.  Adaptive sliding mode control for roll motions of ships , 2008, 2008 International Conference on Control, Automation and Systems.

[46]  Jing Sun,et al.  Path following of underactuated marine surface vessels using line-of-sight based model predictive control ☆ , 2010 .

[47]  G. N. Roberts,et al.  Trends in marine control systems , 2008, Annu. Rev. Control..

[48]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[49]  N. Minorsky.,et al.  DIRECTIONAL STABILITY OF AUTOMATICALLY STEERED BODIES , 2009 .

[50]  Marco Bibuli,et al.  Basic navigation, guidance and control of an Unmanned Surface Vehicle , 2008, Auton. Robots.

[51]  Roger Skjetne,et al.  Line-of-sight path following of underactuated marine craft , 2003 .

[52]  Robert Sutton,et al.  A Review of Guidance Laws Applicable to Unmanned Underwater Vehicles , 2003, Journal of Navigation.

[53]  Feng-Hu Wang,et al.  An improved neural network based fuzzy self-adaptive KALMAN filter and its application in cone picking robot , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[54]  K. D. Do,et al.  Global tracking control of underactuated ships with nonzero off-diagonal terms in their system matrices , 2005, Autom..

[55]  Thor I. Fossen,et al.  A survey on Nonlinear Ship Control: from Theory to Practice , 2000 .

[56]  Farbod Fahimi,et al.  Experimental test of a robust formation controller for marine unmanned surface vessels , 2010, Auton. Robots.

[57]  伊藤 辰雄 International regulations for preventing collisions at sea , 1936 .

[58]  David F. Rogers,et al.  THE SOCIETY OF NAVAL ARCHITECTS AND MARINE ENGINEERS , 1977 .

[59]  Damir Vučina,et al.  Model Update with Observer/Kalman Filter and Genetic Algorithm Approach , 2012 .

[60]  Robert Sutton,et al.  Advances in Unmanned Marine Vehicles , 2006 .

[61]  Gudrun Høye,et al.  Maritime traffic monitoring using a space-based AIS receiver , 2006 .