A Novel Fast Marching Approach for COLREGS Compliant Dynamic Obstacle Avoidance for Unmanned Surface Vehicles
Rik Oude Grote bevelsborg (TU Delft - Mechanical Engineering)
Giulia Giordano – Mentor (TU Delft - Team Tamas Keviczky)
Ton van den Van Den Boom – Graduation committee member (TU Delft - Team Bart De Schutter)
M. Kok – Graduation committee member (TU Delft - Team Jan-Willem van Wingerden)
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Abstract
Successful implementation of fully autonomous vehicles is a much desired objective. Within the area of unmanned marine craft or unmanned surface vehicles (USV), the implementation of truly autonomous navigation is still a challenge. During times in which humans are still actively involved in the processof maritime navigation, regulations are needed to prevent accidents from happening. It is therefore essential for the transition towards more autonomy that USVs are able to obey the regulations as well and clearly exhibit the right behavior to enable other ships to anticipate the behavior of USVs and reactappropriately and timely. In maritime navigation, ships have to obey the International Regulations for preventing collisions at sea, also known as COLREGS (COLlision REGulationS). This thesis is focused on the guidance of USVs, and is specifically aimed at COLREGS compliant path re-planning to avoid potential collisions. A first method has been conceived based upon the SaturatedFast Marching Square method where trailing points are used to correctly guide the USV past dynamic vessels according to COLREGS. A second novel method builds upon the previous one, by combining the Saturated Fast Marching Square method with a path generating Genetic Algorithm. The first methodperforms as supposed in simple environments such as when encountering a single dynamic obstacle. However, the first method starts to under-perform as complexity increases through the presence of both static and dynamic obstacles. The additional second method performs accurately in complex scenariosas well. Both methods have been tested in single case simulations and in extensive random simulations to assess their COLREGS compliant path re-planning accuracy.