TY - GEN
T1 - Recovery Path Planning for Autonomous Underwater Vehicles Using Constrained Bi-RRT∗-Smart Algorithms
AU - Zhang, Zhenchi
AU - Wu, Haibo
AU - Zhou, Heng
AU - Song, Yunxuan
AU - Chen, Yimin
AU - He, Ke
AU - Gao, Jian
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In this paper, a constrained bi-RRT∗-smart algorithm is proposed to solve the recovery path planning problem of an Autonomous Underwater Vehicle (AUV). The RRT∗-smart algorithm is taken as a basic strategy for the predefined path-planning problem to generate an optimal path which has the smallest distance and no collisions with the islands. On this basis, a bi-direction technique is fusion with the RRT∗-smart algorithm to get a bi- RRT∗-smart algorithm. Additionally, two practical constraints are considered to facilitate the feasibility of the proposed method in real applications. For one thing, considering the limited turning ability of the AUV. For another, a local direction constraint is set near the ending point to ensure that the AUV enters the docking station along a reasonable direction. Compared with the previous algorithms, it not only reduces the path cost, but also greatly improves the convergence rate. Simulation results confirm the efficiency of the proposed bi-RRT∗- smart algorithm.
AB - In this paper, a constrained bi-RRT∗-smart algorithm is proposed to solve the recovery path planning problem of an Autonomous Underwater Vehicle (AUV). The RRT∗-smart algorithm is taken as a basic strategy for the predefined path-planning problem to generate an optimal path which has the smallest distance and no collisions with the islands. On this basis, a bi-direction technique is fusion with the RRT∗-smart algorithm to get a bi- RRT∗-smart algorithm. Additionally, two practical constraints are considered to facilitate the feasibility of the proposed method in real applications. For one thing, considering the limited turning ability of the AUV. For another, a local direction constraint is set near the ending point to ensure that the AUV enters the docking station along a reasonable direction. Compared with the previous algorithms, it not only reduces the path cost, but also greatly improves the convergence rate. Simulation results confirm the efficiency of the proposed bi-RRT∗- smart algorithm.
KW - autonomous underwater vehicles
KW - bi-RRT-smart algorithm
KW - local direction constraint
KW - recovery path planning
UR - http://www.scopus.com/inward/record.url?scp=85173687511&partnerID=8YFLogxK
U2 - 10.1109/OCEANSLimerick52467.2023.10244454
DO - 10.1109/OCEANSLimerick52467.2023.10244454
M3 - 会议稿件
AN - SCOPUS:85173687511
T3 - OCEANS 2023 - Limerick, OCEANS Limerick 2023
BT - OCEANS 2023 - Limerick, OCEANS Limerick 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 OCEANS Limerick, OCEANS Limerick 2023
Y2 - 5 June 2023 through 8 June 2023
ER -