Renato Jorge Silva

Abstract
Autonomous Surface Vehicles (ASVs) provide the ideal platform to further explore the many opportunities in the cargo shipping industry, by making it more profitable and safer. This paper presents an architecture for the autonomous docking operation, formed by two stages: a maneuver module and, a situational awareness system to detect a mooring facility where an ASV can safely dock. Information retrieved from a 3D LIDAR, IMU and GPS are combined to extract the geometric features of the floating platform and to estimate the relative positioning and orientation of the moor to the ASV. Then, the maneuver module plans a trajectory to a specific position and guarantees that the ASV will not collide with the mooring facility. The approach presented in this paper was validated in distinct environmental and weather conditions such as tidal waves and wind. The results demonstrate the ability of the proposed architecture for detecting the docking platform and safely conduct the navigation towards it, achieving errors up to 0.107 m in position and 6.58 degrees in orientation.

Abstract
Shipping transportation mode needs to be even more efficient, profitable and secure as more than 80% of the world's trade is done by sea. Autonomous ships will provide the possibility to eliminate the likelihood of human error, reduce unnecessary crew costs and increase the efficiency of the cargo spaces. Although a significant work is being made, and new algorithms are arising, they are still a mirage and still have some problems regarding safety, autonomy and reliability. This paper proposes an online obstacle avoidance algorithm for Autonomous Surfaces Vehicles (ASVs) introducing the reachability with the protective zone concepts. This method estimates a collision-free velocity based on inner and outer constraints such as, current velocity, direction, maximum speed and turning radius of the vehicle, position and dimensions of the surround obstacles as well as a movement prediction in a close future. A non-restrictive estimative for the speed and direction of the ASV is calculated by mapping a conflict zone, determined by the course of the vehicle and the distance to obstacles that is used to avoid imminent dangerous situations. A set of simulations demonstrates the ability of this method to safely circumvent obstacles in several scenarios with different weather conditions.