Autonomous Sailboat Navigation

The purpose of this study was to investigate novel methods on an unmanned sailing boat, which enables it to sail fully autonomously, navigate safely, and perform long-term missions. The author used robotic sailing boat prototypes for field experiments as his main research method. Two robotic sailing boats have been developed especially for this purpose. A compact software model of a sailing boat's behaviour allowed for further evaluation of routing and obstacle avoidance methods in a computer simulation. The results of real-world experiments and computer simulations are validated against each other. It has been demonstrated that autonomous boat sailing is possible by the effective combination of appropriate new and novel techniques that will allow autonomous sailing boats to create appropriate routes, to react properly on obstacles and to carry out sailing manoeuvres by controlling rudder and sails. Novel methods for weather routing, collision avoidance, and autonomous manoeuvre execution have been proposed and successfully demonstrated. The combination of these techniques in a layered hybrid subsumption architecture make robotic sailing boats a promising tool for many applications, especially in ocean observation

Development and test of an open source autonomous sailing robot with accessibility, generality and extendability

This paper introduces the design of an open source autonomous sailing robot with emphasis on its accessibility, generality and extendability. To meet such requirements, a generic control box connecting an Arduino board and a Raspberry Pi computer was tailor-made so as to host the robot operating system (ROS) and to interact with versatile sensors and actuators. The goal of such a project is to create an accessible, generic and expendable platform of autonomous sailboats for wider education and research publicity and engagement. Autonomous sailing test for the developed sailboat was also conducted to validate its design

Modelling and design of an autonomous sailboat for ocean observation

Includes bibliographical references.This study presents various aspects of the development of an autonomous sailboat for ocean observation, with specific focus on modelling and simulation. The potential value of such platforms for ocean observation is well established, with there being a number of expected advantages over existing solutions. A comprehensive literature review is presented, revealing that the modelling of sailboats is an existing field but that the modelling of small autonomous platforms appears to have been limited. This study develops three and four degree of freedom models of a small autonomous J-Class style sailboat. The sailboat is a prototype platform which is developed from its existing state as part of the study. Both models are validated against data logged during field tests, showing broad agreement with some limitations being noted. Results of simulations of the models are used to draw a number of conclusions regarding the appropriate design of the platform's wing-sail, the wing-sail's control requirements in diffirent wind conditions, potential modifications of the platform's design, and the control of its heading while sailing. Results are also used to inform the proposal of a novel 'variable draft sailing spar' as an alternative autonomous sailboat design

Graph-Search and Differential Equations for Time-Optimal Vessel Route Planning in Dynamic Ocean Waves

Time-optimal paths are evaluated by VISIR (\u201cdis- coVerIng Safe and effIcient Routes\u201d), a graph-search ship routing model, with respect to the solution of the fundamental differential equations governing optimal paths in a dynamic wind-wave environment. The evaluation exercise makes use of identical setups: topological constraints, dynamic wave environmental conditions, and vessel-ocean parametrizations, while advection by external currents is not considered. The emphasis is on predicting the time-optimal ship headings and Speeds Through Water constrained by dynamic ocean wave fields. VISIR upgrades regarding angular resolution, time-interpolation, and static nav- igational safety constraints are introduced. The deviations of the graph-search results relative to the solution of the exact differential equations in both the path duration and length are assessed. They are found to be of the order of the discretization errors, with VISIR\u2019s solution converging to that of the differential equation for sufficient resolution

Position keeping control of an autonomous sailboat

International audienceThis paper addresses the problem of reaching and keeping a target position for a sailboat. A method to control sail angle is proposed, using an adaptive adjustment of the sail to regulate the acceleration of the sailboat. A tacking strategy is defined to navigate into the wind, arrive upwind to slow down the boat and then to stay close to the target point. Simulation results show the effectiveness of the proposed approach. The stability of the sailboat using the proposed control has been proven

A Robust Reactive Static Obstacle Avoidance System for Surface Marine Vehicles

This paper is centered on the guidance systems used to increase the autonomy of unmanned surface vehicles (USVs). The new Robust Reactive Static Obstacle Avoidance System (RRSOAS) has been specifically designed for USVs. This algorithm is easily applicable, since previous knowledge of the USV mathematical model and its controllers is not needed. Instead, a new estimated closed-loop model (ECLM) is proposed and used to estimate possible future trajectories. Furthermore, the prediction errors (due to the uncertainty present in the ECLM) are taken into account by modeling the USV's shape as a time-varying ellipse. Additionally, in order to decrease the computation time, we propose to use a variable prediction horizon and an exponential resolution to discretize the decision space. As environmental model an occupancy probability grid is used, which is updated with the measurements generated by a LIDAR sensor model. Finally, the new RRSOAS is compared with other SOA (static obstacle avoidance) methods. In addition, a robustness study was carried out over a set of random scenarios. The results obtained through numerical simulations indicate that RRSOAS is robust to unknown and congested scenarios in the presence of disturbances, while offering competitive performance with respect to other SOA methods

Genetic algorithm-based multiple moving target reaching using a fleet of sailboats

International audienceThis study addresses the problem of Dynamic Travelling Salesman Problem for a multi-agent system using a fleet of sailboats. A genetic algorithm (GA) is proposed, which attributes to each agent a varying number of targets to be collected. GA allows obtaining a suboptimal solution in the shortest time possible. Moreover, this study adapts it to the specific problem involving a fleet of sailboats, which is a challenging task with comparison to autonomous underwater vehicles or motorised vehicles in terms of the propulsion. Therein motors can be flexibly controlled while sailboat movements are constrained by available wind direction and speed. Thus the method takes into account wind conditions at various locations of the sailboat. Simulation results demonstrate the effectiveness of the proposed approach

A Real-Time Game Theoretic Planner for Autonomous Two-Player Drone Racing

To be successful in multi-player drone racing, a player must not only follow the race track in an optimal way, but also compete with other drones through strategic blocking, faking, and opportunistic passing while avoiding collisions. Since unveiling one's own strategy to the adversaries is not desirable, this requires each player to independently predict the other players' future actions. Nash equilibria are a powerful tool to model this and similar multi-agent coordination problems in which the absence of communication impedes full coordination between the agents. In this paper, we propose a novel receding horizon planning algorithm that, exploiting sensitivity analysis within an iterated best response computational scheme, can approximate Nash equilibria in real time. We also describe a vision-based pipeline that allows each player to estimate its opponent's relative position. We demonstrate that our solution effectively competes against alternative strategies in a large number of drone racing simulations. Hardware experiments with onboard vision sensing prove the practicality of our strategy

A novel approach of collision assessment for coastal radar surveillance

For coastal radar surveillance, this paper proposes a data-driven approach to estimate a blip’s collision probability preliminarily based on two factors: the probability of it being a moving vessel and the collision potential of its position. The first factor can be determined by a Directed Acyclic Graph (DAG), whose nodes represent the blip’s characteristics, including the velocity, direction and size. Additionally, the structure and conditional probability tables of the DAG can be learned from verified samples. Subsequently, the obstacles in a waterway can be described as collision potential fields using an Artificial Potential Field model, and the corresponding coefficients can be trained in accordance with the historical vessel distribution. Then, the other factor, the positional collision potential of any position is obtained through overlapping all the collision potential fields. For simplicity, moving speeds of obstacles are considered in this research. Eventually, the two factors are characterised as two pieces of evidence, and the collision probability of a blip is estimated by combining them with Dempster’s rule. Through ranking blips on collision probabilities, those that pose high threat to safety can be picked up in advance to remind supervisors. Particularly, a good agreement between the proposed approach and the manual work was found in a preliminary test