Due to the extremely vast area of the maritime environment, autonomous robotic systems have been heavily demanded to reduce risk to human and increase efficiency. A large number of such demands remain on the marine surface, such as ocean upper layer observation, pollution detection, patrolling, and communication. Vastness of the ocean has placed significant challenges on marine surface robots for long-term operation, especially from perspectives of energy. Sailing robots can contribute significantly to maritime surface exploration, due to its potential for long-range and long-duration motions in the environment with abundant wind.

We have explored sailing robot with various sizes, including mini sailboats for educational purpose with controlled wind field and indoor water pool, and large-scaled sailboat with capability of long-term marine test. Risk avoidance is also investigated to make the robot safer.

1. Mini sailboat with STAr (Sailboat Test Arena)

We have developed various mini sailboats in length of about 30cm -1m, and established a shareable, inexpensive, easy operated, efficient and remotely accessible test platform, named Sailboat Test Area (STAr). STAr has three remotely accessible modes.

Figure 1. STAr architecture and user interface

From the local experiments, Various research topics have been conducted in STAr. Through a large number of local and remote experiments, the feasibility, robustness and high efficiency of STAr have been verified.

Figure 2. Internet server framework of STAr and a remote sailing test

STAr contributes to provide a remote control solution for sailing robots and an open platform for researchers to access. All relevant materials can be found at https://github.com/star-cuhksz/STAr. All the sailboat data, including location, attitude, speed, sail and rudder commands can be recorded for further analysis of the robot dynamics.

2. OceanVoy and energy management

We have designed a 3.1m long autonomous catameram named OceanVoy310, and further investigated an energy-saving approach named E-saving method.

Figure 3. OceanVoy and the updated strategy for E-saving in the vector field

Our E-saving methodology has two key features. First, it focuses on analyzing the vector field around OceanVoy to generate a heading that is confined to the stability zone. We explored a suitable tradeoff between path tracking error and energy consumption. Based on that, we modify the baseline control method by adding an error vector, which determines the updating of the desired heading. Second, we fine-tune the parameters in low-level control with a PID controller, which is robust in the marine environment and generates fewer output signals.

Figure 4. Experiment of tracking three lines in a complex scenario

We implement the baseline (V-stability) method and the E-saving method in simulations and experiments. The results show that both methods afford good path-following performance, while the E-saving method achieves substantial energy savings during sailing, i.e., an approximately 11% saving in experiment with OceanVoy.

3. Risk avoidance

OceanVoy 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.

Figure 5. OceanVoy in the sea with encounter scenario and collision avoidance scheme

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.

Figure 6. The configurations of OceanVoy and experiment result

Another risk to robotic sailboats is the wakes, which may lead to capsizing. We proposed a Kelvin wake-avoidance scheme for the autonomous sailboat. It involves wake modeling, wake avoidance scheme designing and developing based on an orientation-restricted Dubins path and path tracking.

Figure 7. OceanVoy sailing in the sea with ship wake and the proposed avoidance scheme

The quantitative data reveal that the maximum range of roll is reduced by 57.4% in "alongside" scenario. In "toward" scenario, the maximum roll range is kept acceptable, while max range of surge acceleration is decreased by 23.4%.

Figure 8. Experiments in open sea for avoiding the toward Kelvin wake

4. Station keeping

We define an ocean observation mission in a restricted target area as a station keeping problem. Inspired by an orientation-restricted Dubins path method, the robot keeps sailing and collecting data in a smooth reciprocation, where the trajectories consist of sailing against wind segments and turning downwind parts divided by a goal area and an acceptable area. We completed continuous and effective observation within 50 minutes in the goal area with a radius of 50 meters by a improved catamaran robot, OceanVoy460.

Figure 9. Overview of the stable station keeping scheme and switched system

Figure 10. Experiment results

Selected publications:

1. Weimin Qi, Qinbo Sun, Yu Cao, and Huihuan Qian*, “Stable station keeping of autonomous sailing robots via the switched systems approach for ocean observation”, 2023 IEEE International Conference on Robotics and Automation (ICRA), London, UK, 2023. (Accepted)
2. Qinbo Sun, Weimin Qi, Cheng Liang, Bairun Lin, Francesco Maurelli, and Huihuan Qian*, “Sailboat Test Arena (STAr): a remotely accessible platform for robotic sailboat research”, Journal of Marine Science and Engineering, Vol. 11, No. 297, pp. 1-16, February 1, 2023. 
3. Qinbo Sun, Weimin Qi, Xiaoqiang Ji, and Huihuan Qian*, “V-stability based control for energy-saving towards long range sailing”, IEEE Robotics and Automation Letters (RA-L), Vol. 8, No. 1, pp. 328-335, January, 2023.
4. Weimin Qi, Qinbo Sun, Xiaoqiang Ji, Yiwen Liang, Zhongzhong Cao, and Huihuan Qian*, “A Kelvin wake avoidance scheme for autonomous sailing robots based on orientation-restricted Dubins path”, IEEE Robotics and Automation Letters (RA-L), Vol. 7, No. 4, pp. 11585-11592, October, 2022. 
5. Qinbo Sun, Weimin Qi, Hengli Liu, Xiaoqiang Ji, and Huihuan Qian*, “Towards long-term sailing robots: state of the art from energy perspectives”, Frontiers in Robotics and AI, Vol. 8, pp. 1-24, January 5, 2022. 
6. Weimin Qi, Qinbo Sun, Chongfeng Liu, Xiaoqiang Ji, Zhongzhong Cao, Yiwen Liang, and Huihuan Qian*, “Collision risk assessment and obstacle avoidance control for autonomous sailing robots”, 2021 IEEE International Conference on Robotics and Automation (ICRA), pp. 2511-2517, Xi’an, China, May 31 – June 4, 2021.
7. Qinbo Sun, Weimin Qi, Hengli Liu, Zhenglong Sun, Tin Lun Lam, and Huihuan Qian*, “OceanVoy: a hybrid energy planning system for autonomous sailboat”, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2481-2487, Las Vegas, USA, October 25-29, 2020. [Best Application Paper Finalist]