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Ensuring an adequate supply of energy is a challenge in the development of autonomous sailboats for long-range sailing capability, as the continuous high-frequency execution of control commands leads to high energy consumption. However, as the control of sailboat is much more complex than the other USVs, especially in a complicated and windy environment, simply reducing control frequency will lead to large path tracking error, and even unsuccessful navigation. Based on the V-stability controller of sailboats, this paper proposes an energy-saving (E-saving) control scheme for a sailboat, to enable the energy planning of actuators. While keeping the sailboat traveling within the acceptable range along a desired path, we develop an approach to analyze and reach a satisfying tradeoff between path tracking error and consumed energy. The E-saving method is examined in simulated environments and field experiments using an autonomous sailboat (OceanVoy). The results show that E-saving method reduces energy consumption by approximately 11% compared to that of the previous V-stability controller, indicating that our method can elongate sailing distance.

Sailboats have a wide range of applications on account of their energy-saving, environmentally benign and lownoise characteristics. This has led to the increasing popularity of research in autonomous sailing robots, with concomitant attention paid to the development of methods that ensure their safety during sailing. Sailboats are affected by obstacles and by nonlinear aerodynamic and hydrodynamic factors. In particular, sailboats are affected by the wake generated by a moving vessel, which in this paper is denoted a moving boat. Wakes are swift and can have severe adverse effects on a sailboat by causing it to veer off course, stall or capsize. Moreover, sailboats have low mobility and large inertia, and will therefore struggle to avoid a wake. Thus, in this paper, we describe our efforts to develop a method to enable a sailboat to perform wake avoidance. We model the wake as a Kelvin wake, and generate waypoints for an orientation-restricted Dubins path-based Kelvin wake-avoidance method. A V-stability-based control method has proven suitable for generating the path, after which the desired heading angle for sailboat control is obtained. The resulting wake-avoidance method is verified in simulations and experiments. It enables the sailboat to avoid alongside and toward wakes, and the qualitative results has revealed that the maximum range of roll in alongside scenario and maximum range of surge acceleration in toward scenario is reduced by 57.4% and 23.4%, respectively, relative to a situation when no wake-avoidance method was used. The maximum range of roll in toward scenario is acceptable.

The ship wake affects the motion of Unmanned Surface Vehicles (USVs) essentially. While USV simulators have been proposed recently, they do not support the ship wake. In this paper, a computational efficient simulation of ship wake is proposed. The simulation is based on influence-point model. In some portion of the wake, this model is inaccurate. Extra processes are applied to pre-manipulate the model to ensure its accuracy. The simulation can be applied to a general scenario, especially when the ship velocity varies with time. The results show that the wake is accurate, and the computational complexity is low. The simulated wake has been equipped into a USV simulator, providing a more realistic environment disturbance.

Obstacle avoidance is crucial for autonomous surface vehicles (ASVs) in the sea because rescue is extremely difficult there. OceanVoy, a sailboat toward long range energy-saving voyage, has to overcome the dual challenges, i.e. from the environmental interference and its low mobility preventing from precise obstacle avoidance. We propose a control scheme based on real-time collision risk assessment and a hybrid propulsion system to enhance safety of OceanVoy. A novel sailboat safety zone (SSZ) has been designed to warn the potential collision during its sailing. Both intrinsic characteristics of OceanVoy and environmental factors have been considered in SSZ. We use lateral and axial thrusters to provide emergency propulsion. A collision avoidance algorithm is executed to coordinate motors in rudder, sail and thrusters based on SSZ. Both simulation and experiments have been conducted and the results have validated our system and collision avoidance scheme.

This paper proposes a drive-through recharging strategy for a quadrotor. First, a ground charging station is constructed with a portable charging wire, then with two conductive hooks connected to the battery, the quadrotor is flying through the station. Finally, after connecting the hooks to the charging wire, the quadrotor can be recharged without landing or stopping, similar to a drive-through. During the charging, the quadrotor is still able to accomplish local monitoring assignments. The main challenge of this work is to ensure that the hooks successfully connect to the charging wire. Though visual-based techniques appear promising to handle this problem, the detection of a thin charging wire is challenging especially during the flight. Besides, the conductive hooks underneath the quadrotor are out of the camera view, which brings more challenges to the problem. Therefore, in this paper, the aiming problem is directed into the position constraint control problem of the quadrotor. Specifically, a virtual aiming box is considered near the charging wire center, then a control design is proposed to constrain the position of the quadrotor to ensure the hooks position always within the virtual aiming box. Moreover, to enhance the system robustness against the outdoor environment, a wind disturbance estimator is proposed in the control design. Both theoretical analysis and experimental validation are carried out to demonstrate the effectiveness of the proposed strategy.

Towards long range and high endurance sailing, energy is of utmost importance. Moreover, benefiting from the dominance of the sailboat itself, it is energy-saving and environment-friendly. Thus, the sailboat with energy planning problem is meaningful. However, until now, the sailboat energy optimization problem has rarely been considered. In this paper, we focus on the energy consumption optimization of an autonomous sailboat. It has been formulated as a Nonlinear Programming problem (NLP). We deal with it with a hybrid control scheme, in which pseudo-spectral (PS) optimal control method is used in heading control, and a model-free framework guided by Extreme Seeking Control (ESC) is used in sail control. The optimal path is generated with the optimal input motor torques in time series. As a result, both simulation and experiments have validated motion planning and energy planning performance. Notably, about 7% of energy is saved on average. Our proposed method can make sailboats sailing longer and sustainable.

Obstacle avoidance of autonomous sailboats is a complicated task due to big inertia, highly nonlinear motion of sailboat and uncertain disturbance from wind and water current. To deal with the obstacle avoidance problem of autonomous sailboats, we promote a novel method based on reinforcement learning with coarse-to-fine strategy. In this strategy, coarse stage is used to detect the autonomous sailboat roughly in the test environment. Then fine stage is applied to localize the autonomous sailboat accurately. Hereby, the avoidance performance is improved by the transition from coarse to fine. We have verified our algorithms both in simulation and real experiments. With our method, the sailboat avoids the obstacle in higher precision than the method without the coarse-to-fine strategy. The final success rate of obstacle avoidance is near 83% and the rate of reaching goal is 70%. Both simulation results and experiments show that our method is effective.

This paper describes a low-cost, wide-range and multi-functional vision backend for Sailboat Research Testbed (SRT). SRTs are of great significance in autonomous sailing vessels (ASVs) research. The motivation behind this vision backend is the demand for various functions of an SRT, such as sailboat localization and control, yet the cost of building such a testbed should be economic. Hence, cost-effective hardware along with robust and lightweight vision algorithms are integrated into a vision backend to assist our SRT. This vision backend overcomes several inherent problems when applying some CV algorithms in the water environment, and presents multiple functionalities with high performance. This paper details our solutions and design of this vision backend. Moreover, a variety of schemes are introduced to reduce the cost when building SRTs.

Autonomous Surface Vehicles (ASVs) provide an effective way to actualize applications such as environment monitoring, search and rescue, and scientific researches. However, the conventional ASVs depends overly on the stored energy. Hybrid Sailboat, mainly powered by the wind, can solve this problem by using an auxiliary propulsion system. The electric energy cost of Hybrid Sailboat needs to be optimized to achieve the ocean automatic cruise mission. Based on adjusted setting on sails and rudders, this paper seeks the optimal trajectory for autonomic cruising to reduce the energy cost by changing the heading angle of sailing upwind. The experiment results validate the heading angle accounts for energy cost and the trajectory with the best heading angle saves up to 23.7% than other conditions. Furthermore, the energy-time line can be used to predict the energy cost for long-time sailing., 6pages, IEEE ROBIO 2018, accpeted

This paper introduces the tacking control of a low-cost mini-sized unmanned catamaran sailboat. Compared with traditional researches in sailboats based on acquiring wind speed and direction by a giant wind sensor and controlling the system by velocity polar diagram, to further increase the speed and motion agility, we propose an alternative way based on Force Polar Diagram (FPD). Thereafter, we propose a novel control algorithm to compute the sail angle that produces the maximum forward force along the boat‘s heading. We employ a 3-D force sensor to obtain the propelling force on the mast. FPD is created offline given the data collected from different apparent wind angles. In the experimental platform including a water pool, two electric fans generating a quasi-controllable time-invariant wind field and a camera for boat Iocalization, we conducted experiments and discovered that the proposed method increased the maximum speed by 56%, shortened the time by 44% and improved the motion agility in an autonomous tacking for upper wind motion.

Multi-sensor optimal allocation is significant for mobile robot navigation, and its perception robustness is an important performance standard for multi-sensor system. Thus this paper designs sensors optimal allocation model and defines a robustness evaluation fitness function. Meanwhile, an improved DPSO algorithm is proposed to solve the sensors coalition allocation with the best robustness. Firstly, a multi-sensor optimal allocation model is devised with single sensor level constraint and sensor coalition level constraint. Secondly, an improved DPSO with new updating mechanism is developed for sensors coalition with the best robustness. Furthermore, the particles updating mechanism is redefined, which composed of 0 and 1 binaries of DPSO position element. Finally, heterogeneous sensors allocation experiments are analyzed in order to show the feasibility and effectiveness of improved DPSO. Those experiments show the sensor coalition work smoothly and efficiently, even though several sensors are damaged. Additionally, the advantages of our model and algorithm is proved by comparison experiments.