3D AUV Collision Avoidance

An underlying requirement for any Autonomous Underwater Vehicle (AUV) is to navigate through unknown or partly unknown environments while performing certain user specified tasks. The loss of an AUV due to collision is unjustifiable both in terms of cost and replacement time. To prevent such an unfortunate event, one requires a robust and effective Collision Avoidance System (CAS). This paper discusses the collision avoidance problem for the HUGIN AUVs. In the first part, a complete simulator for the HUGIN AUV is implemented in matlab and simulink. This includes a 6 degrees-of-freedom nonlinear AUV model, simulated environment including bottom profile and surface ice, navigation- and guidance functionality and sensor simulators. In the second part a number of well known strategies for the collision avoidance problem is presented with a short analysis of their properties. On the basis of the implemented simulator, a proposed CAS is developed and it’s performance is analyzed. This system is based on simple principles and known collision avoidance strategies, in order to provide effective and robust performance. The proposed system provides feasible solutions during all simulations and the collision avoidance maneuvers are performed in accordance with the specified user demands. The developed simulator and collision avoidance system is expected to provide a suitable framework for further development and possibly a physical implementation on the HUGIN AUVs

Low Altitude Georeferencing for Imaging Sensors in Maritime Tracking

This paper presents a method for georeferencing low-altitude camera sensors, both infrared and electro-optical, in a maritime context. Accurate georeferencing require very high precision for the object pixel coordinates due to sensor resolution. To achieve this we refine the bounding boxes provided by an SSD object detector using the Sobel operator and the Hough transform. Using real world data this method is applied in a maritime tracking system based on the Joint Integrated Probabilistic Data Association method and compared to radar tracking. The georeferenced cameras surpassed radar performance in several of the benchmarks and maintained tracks with greater reliability at the cost of reduced position accuracy

Sensor Combinations in Heterogeneous Multi-sensor Fusion for Maritime Target Tracking

Safe navigation for autonomous surface vehicles requires a robust and reliable tracking system that maintains and estimates position and velocity of other vessels. This paper demonstrates a measurement level sensor fusion system for tracking in a maritime environment using lidar, radar, electrooptical and infrared cameras. The backbone of the system is a multi-sensor version of the Joint Integrated Probabilistic Data Association (JIPDA) with both existence and visibility probabilities. Using reference targets equipped with GPS receivers, the performance of different sensors and sensor combinations are evaluated for autonomous surface vehicles (ASVs), Several interesting observations are made, among them that passive sensors can help resolve merged measurements issues in radar tracking, and that the choice between radar and lidar may boil down to a trade-off between fast track initiation and large numbers of false tracks

AIS-based near-collision database generation and analysis of real collision avoidance manoeuvres

Economic and technological development has increased the amount, density and complexity of maritime traffic, which has resulted in new challenges. One challenge is conforming to the distinct evasion manoeuvres required by vessels entering into near-collision situations (NCSs). Existing rules are vague and do not precisely dictate which, when and how collision avoidance manoeuvres (CAMs) should be executed. The automatic identification system (AIS) is widely used for vessel monitoring and traffic control. This paper presents an efficient, scalable method for processing large-scale raw AIS data using the closest point of approach (CPA) framework. NCSs are identified to create a database of historical traffic data. Important features describing CAMs are defined, estimated and analysed. Applications on a high-quality real-world data set show promising results for a subset of the identified situations. Future applications may play a significant role in the maritime regulatory framework, navigation protocol compliance evaluation, risk assessment, automatic collision avoidance, and algorithm design and testing for autonomous vessels

AIS-Based Multiple Vessel Collision and Grounding Risk Identification based on Adaptive Safety Domain

The continuous growth in maritime traffic and recent developments towards autonomous navigation have directed increasing attention to navigational safety in which new tools are required to identify real-time risk and complex navigation situations. These tools are of paramount importance to avoid potentially disastrous consequences of accidents and promote safe navigation at sea. In this study, an adaptive ship-safety-domain is proposed with spatial risk functions to identify both collision and grounding risk based on motion and maneuverability conditions for all vessels. The algorithm is designed and validated through extensive amounts of Automatic Identification System (AIS) data for decision support over a large area, while the integration of the algorithm with other navigational systems will increase effectiveness and ensure reliability. Since a successful evacuation of a potential vessel-to-vessel collision, or a vessel grounding situation, is highly dependent on the nearby maneuvering limitations and other possible accident situations, multi-vessel collision and grounding risk is considered in this work to identify real-time risk. The presented algorithm utilizes and exploits dynamic AIS information, vessel registry and high-resolution maps and it is robust to inaccuracies of position, course and speed over ground records. The computation-efficient algorithm allows for real-time situation risk identification at a large-scale monitored map up to country level and up to several years of operation with a very high accuracy

Development of a Dynamic Positioning System for the ReVolt Model Ship

A Dynamic Positioning (DP) control system is developed, implemented and tested for a scale model of DNV GL’s concept ship ReVolt. This model-scale ship is used as a test platform for sensors and control systems used in autonomous vessels, and this paper focuses on the functionality and implementation of the components and control system required to achieve DP capabilities on the ReVolt model ship. The DP system consists of a 3-Degree of Freedom reference filter, Proportional-Integral-Derivative (PID) controller with a model-based reference feedforward, and a thrust allocation module from DNV GL. The DP system is implemented on ReVolt’s onboard computer, which runs the Robot Operating System (ROS) on top of a Linux shell. Field tests are conducted, with the main objective to achieve station keeping and low-speed maneuvering capabilities for ReVolt. Different setups in the thrust allocation and controller are assessed by performance metrics to determine the best overall setup for ReVolt