Surfing Algorithm: Agile and Safe Transition Strategy for Hybrid Aerial Underwater Vehicle in Waves

• Published in: IEEE transactions on robotics 2023-12, Vol.39 (6), p.4262-4278
• Main Authors: Bi, Yuanbo, Jin, Yufei, Zhou, Hexiong, Bai, Yulin, Lyu, Chenxin, Zeng, Zheng, Lian, Lian
• Format: Article
• Language: English
• Subjects: Algorithms; Controllers; Crossing wave surface; Dynamic models; dynamic window; Energy costs; Flight control systems; Gravity; Heuristic algorithms; hybrid aerial underwater vehicle (HAUV); Hydrodynamics; Inertial platforms; Initial conditions; Locomotion; Prototypes; Robust control; Sea surface; Strategy; Surface waves; Surfing; surfing algorithm (SA); Takeoff; Underwater vehicles; Vehicle dynamics; Wave crest
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2023.3319928

The agile and safe transdomain in waves is a promising feature but the primary bottleneck of the hybrid aerial underwater vehicle (HAUV). In this article, the surfing algorithm is proposed for Nezha-mini, our predeveloped HAUV prototype, to search for the dynamic window facilitating takeoff in waves and avoiding hazardous waves. For the first time, the cross-domain window, i.e., the vehicle is at the wave crest and heading downstream, is characterized and defined through the vehicle-wave coupled dynamic model. The novel surfing algorithm consists of the gradient perceptron, time-limited momentum gradient search, heading server, and initial conditions. Nezha-mini senses, searches, and tracks the dynamic window in real-time, until the takeoff decisions are triggered. Numerical simulations and experiments in regular and irregular waves reveal the effectiveness of the algorithm. The vehicle maintains a healthy initial attitude and inaccessible wave disturbance during takeoff, thus alleviating the thrust distraction from stability recovery and uncertainty. The average transition time and energy cost are reduced by 59.2% and 26.1% compared with random takeoff cases, and the locomotion is smooth, graceful, and low-risk. The computation and cost are low as the algorithm only requires the basic flight controller and the data from the inertial measurement unit instead of the prior parameters of the HAUV and waves. In comparison with the adaptive robust controller, which resists wave disturbance directly, this article provides an enlightening strategy from the perspective of harnessing waves.