The branching‐course model predictive control algorithm for maritime collision avoidance

This article presents a new algorithm for short-term maritime collision avoidance (COLAV) named the branching-course MPC (BC-MPC) algorithm. The algorithm is designed to be robust with respect to noise on obstacle estimates, which is a significant source of disturbance when using exteroceptive sensors such as e.g. radars for obstacle detection and tracking. Exteroceptive sensors do not require vessel-to-vessel communication, which enables COLAV toward vessels not equipped with e.g. automatic identification system (AIS) transponders, in addition to increasing the robustness with respect to faulty information which may be provided by other vessels. The BC-MPC algorithm is compliant with rules 8 and 17 of the International Regulations for Preventing Collisions at Sea (COLREGs), and favors maneuvers following rules 13-15. This results in a COLREGs-aware algorithm which can ignore rules 13-15 when necessary. The algorithm is experimentally validated in several full-scale experiments in the Trondheimsfjord in 2017 using a radar-based system for obstacle detection and tracking. The COLAV experiments show good performance in compliance with the desired algorithm behavior.

[1]  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.

[2]  S. LaValle.  Rapidly-exploring random trees : a new tool for path planning , 1998 .

[3]  Claudio Paliotta.  Control of Under-actuated Marine Vehicles , 2017 .

[4]  Tristan Perez,et al.  Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment , 2016, IEEE Transactions on Intelligent Transportation Systems.

[5]  John J. Leonard,et al.  Nested autonomy for unmanned marine vehicles with MOOS‐IvP , 2010, J. Field Robotics.

[6]  Leigh McCue,et al.  Handbook of Marine Craft Hydrodynamics and Motion Control [Bookshelf] , 2016, IEEE Control Systems.

[7]  John J. Leonard,et al.  A method for protocol‐based collision avoidance between autonomous marine surface craft , 2006, J. Field Robotics.

[8]  Oliver Bittel,et al.  Fast grid based collision avoidance for vessels using A∗ search algorithm , 2012, 2012 17th International Conference on Methods & Models in Automation & Robotics (MMAR).

[9]  Morten Breivik,et al.  MPC-Based mid-level collision avoidance for asvs using nonlinear programming , 2017, 2017 IEEE Conference on Control Technology and Applications (CCTA).

[10]  H Eriksen Bjorn-Olav,et al.  A modified dynamic window algorithm for horizontal collision avoidance for AUVs , 2016 .

[11]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[12]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[13]  Morten Breivik,et al.  A Model-Based Speed and Course Controller for High-Speed ASVs , 2018 .

[14]  Michael T. Wolf,et al.  Safe Maritime Autonomous Navigation With COLREGS, Using Velocity Obstacles , 2014, IEEE Journal of Oceanic Engineering.

[15]  J. Watt.  Collision Avoidance Systems , 1973 .

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

[17]  Axel Hahn,et al.  NMPC-based trajectory tracking and collision avoidance of unmanned surface vessels with rule-based colregs confinement , 2016, 2016 IEEE Conference on Systems, Process and Control (ICSPC).

[18]  Jonathan P. How,et al.  Cooperative Distributed Robust Trajectory Optimization Using Receding Horizon MILP , 2011, IEEE Transactions on Control Systems Technology.

[19]  Erik F. Wilthil,et al.  A Target Tracking System for ASV Collision Avoidance Based on the PDAF , 2017 .

[20]  Satyandra K. Gupta,et al.  Dynamics-aware target following for an autonomous surface vehicle operating under COLREGs in civilian traffic , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  C. Chauvin.  Human Factors and Maritime Safety , 2011, Journal of Navigation.

[22]  Petter Ögren,et al.  A convergent dynamic window approach to obstacle avoidance , 2005, IEEE Transactions on Robotics.

[23]  Francesco Borrelli,et al.  A Unified Approach to Threat Assessment and Control for Automotive Active Safety , 2013, IEEE Transactions on Intelligent Transportation Systems.

[24]  A. Harati-Mokhtari,et al.  Automatic Identification System (AIS): Data Reliability and Human Error Implications , 2007, Journal of Navigation.

[25]  C V Caldwell,et al.  Motion planning for an autonomous Underwater Vehicle via Sampling Based Model Predictive Control , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[26]  Tor Arne Johansen,et al.  MPC-based Collision Avoidance Strategy for Existing Marine Vessel Guidance Systems , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[27]  Bj⊘rn-Olav H. Eriksen,et al.  Radar-based maritime collision avoidance using dynamic window , 2018, 2018 IEEE Aerospace Conference.

[28]  Rafal Szlapczynski,et al.  Review of ship safety domains: Models and applications , 2017 .

[29]  Oskar Levander,et al.  Autonomous ships on the high seas , 2017, IEEE Spectrum.

[30]  T.I. Fossen,et al.  Path following for marine surface vessels , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[31]  Morten Breivik,et al.  Modeling, Identification and Control of High-Speed ASVs: Theory and Experiments , 2017 .

[32]  Morten Breivik,et al.  Short-term ASV Collision Avoidance with Static and Moving Obstacles , 2019, Modeling, Identification and Control: A Norwegian Research Bulletin.

[33]  Michael Blaich,et al.  Collision Avoidance for Vessels Using a Low-Cost Radar Sensor , 2014 .

[34]  Andreas L. Flåten,et al.  Rao-blackwellized particle filter for turn rate estimation , 2017, 2017 IEEE Aerospace Conference.

[35]  Anastasios M. Lekkas,et al.  Hybrid Collision Avoidance for ASVs Compliant With COLREGs Rules 8 and 13–17 , 2019, Frontiers in Robotics and AI.

[36]  Torsten Bertram,et al.  A Model Predictive Approach to Emergency Maneuvers in Critical Traffic Situations , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[37]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[38]  A. N. Cockcroft,et al.  A guide to the collision avoidance rules: International Regulations for Preventing Collisions at Sea 1972, in force 1977 , 1976 .

[39]  Edmund Førland Brekke,et al.  The Neighbor Course Distribution Method with Gaussian Mixture Models for AIS-Based Vessel Trajectory Prediction , 2018, 2018 21st International Conference on Information Fusion (FUSION).

[40]  Odd M. Faltinsen,et al.  Hydrodynamics of High-Speed Marine Vehicles , 2006 .

[41]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..