A real-time local path planning algorithm for the wave glider based on time-stamped collision detection and improved artificial potential field

被引:7
作者
Zhang, Shuai [1 ,2 ]
Sang, Hongqiang [1 ,2 ]
Sun, Xiujun [3 ]
Liu, Fen [1 ,2 ]
Zhou, Ying [3 ,4 ]
Yu, Peiyuan [3 ,4 ]
机构
[1] Tiangong Univ, Sch Mech Engn, Tianjin 300387, Peoples R China
[2] Tiangong Univ, Tianjin Key Lab Adv Mechatron Equipment Technol, Tianjin 300387, Peoples R China
[3] Ocean Univ China, Phys Oceanog Lab, Qingdao 266100, Peoples R China
[4] Ocean Univ China, Inst Adv Ocean Study, Qingdao 266100, Peoples R China
关键词
Wave glider; Dynamic model; Local path planning; Artificial potential algorithm; Dynamic obstacle prediction; Complex marine environment; Obstacle avoidance; AVOIDANCE; TRACKING; USV;
D O I
10.1016/j.oceaneng.2023.115139
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The local path planning technology of wave gliders (WGs) is faced with two inherent difficulties: the impact of the complex marine environment on the path and the weak maneuverability. In this paper, a fusion algorithm based on the time-stamped collision detection (TCD) and the environmental improved artificial potential field (EAPF) is proposed to solve the above problems, which combines the dynamic model of the WG to guide it by generating a desired heading output. The improved APF (IAPF) is developed to solve the problems of local minimum and target unreachability. The influence of the complex marine environment on the WG is considered during dynamic obstacle avoidance, and the proposed EAPF improves the maneuverability of the WG with the help of environmental field, while reducing the impact of the environment on the path. For dynamic obstacle prediction, different dynamic obstacle models are used, and the TCD is proposed to predict the collision risk between WG and dynamic obstacles to adapt to the weak maneuverability of the WG. The simulation results show that the proposed TCD-EAPF can realize the early avoidance of dynamic obstacles and improve the maneuverability of the WG in obstacle avoidance.
引用
收藏
页数:23
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