Trajectory-cell based method for the unmanned surface vehicle motion planning

Du, Zhe; Wen, Yuanqiao; Xiao, Changshi; Huang, Liang; Zhou, Chunhui; Zhang, Fan

doi:10.1016/j.apor.2019.02.005

Cited by 27 publications

(10 citation statements)

References 15 publications

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“…Based on the above-mentioned USV dynamic model and discrete rules, we established the USV trajectory unit using the trajectory unit-based USV motion planning method. 44,45 Table 2 shows the specific trajectory unit library.…”

Section: Trajectory Unit Constructionmentioning

confidence: 99%

“…The experiments of the USV motion planning on narrow waters and complex reef waters are carried out in simulation and practical environment, respectively. The comparative experiments are carried out with the method proposed by Du et al, 45 named Zhe’s method in this study.…”

Section: Experiments and Analysismentioning

confidence: 99%

“…42,43 However, their methods did not solve the problem that USV motion planning applied in the restricted water environment. Z Du et al 44 established trajectory units and considered the dynamic requirements of USV, and finally proposed a motion planning algorithm for USV in free waters, and based on the literature, 44 Z Du et al 45 further proposed the 32-directional USV trajectory unit and a new A* motion planning for an USV in free waters.…”

Section: Introductionmentioning

confidence: 99%

“…In a dynamic process of the USV path planning, the first thing is to consider the dynamic constraints and motion state constraints of the USV when sailing in restricted waters. However, the existing approaches did not work well in restricted waters because they did not process the dynamics, 30,39,40,42,43 or consider search algorithm feature to achieve motion planning, 41,44,45 for an USV.…”

Section: Introductionmentioning

confidence: 99%

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A motion planning method for unmanned surface vehicle in restricted waters

Zhou

Wen

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part M:

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The maneuvering characteristics of the unmanned surface vehicle itself are very important to motion planning due to the limited water scale area. If the size, motion state, and maneuvering characteristics of the unmanned surface vehicle are not considered, the shortest path obtained is actually not feasible in the restricted waters. In this article, the widely used A* algorithm is improved by accounting for the maneuvering characteristics of the unmanned surface vehicle, named as the Label-A* Algorithm, which is further employed to fix the problem related to the motion planning for the unmanned surface vehicle in restricted waters. The solution to the motion planning mainly contains three stages. First, the unmanned surface vehicle trajectory unit library is established based on its maneuvering characteristics; second, an improved label-A* Algorithm is constructed, and the unmanned surface vehicle motion planning method is proposed with the trajectory unit, which is suitable for the restricted waters; Finally, numerical simulations and filed tests are designed to verify the formulated model and proposed algorithm. The motion planning method can simultaneously meet the state constraints, maneuvering characteristics constraints, and water scale constraints of unmanned surface vehicle.

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Section: Trajectory Unit Constructionmentioning

confidence: 99%

Section: Experiments and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A motion planning method for unmanned surface vehicle in restricted waters

Zhou

Wen

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part M:

Self Cite

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“…And the A* algorithm was also tried to comply with COLREGS for the way point navigation in an environment cluttered with static and moving obstacles [29]. Considering the dynamic constrains, Du et al [30] propose a trajectory-cell based method to guarantee the final spliced path continuous for the motion planning of USV by determining the cost function of the A* algorithm, although the path obtained is continuous, it does not avoid dynamic obstacles which may cause the USV to collide with dynamic obstacles. Another new work [31] is found that the A* algorithm can be applied to the path planning of USV in sea environment with surface currents by modifying the heuristic function.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Path Planning Algorithm for Unmanned Surface Vehicles in Complex Environment With Dynamic Obstacles

Chen

Zhang

et al. 2019

IEEE Access

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Unmanned surface vesssel (USV) has been widely applied due to its advantages in the military reconnaissance and resources exploration. Path planning is one of the critical issues for USV applications, which usually includes global and local path planning methods. However, individual global path planning algorithms may not be easy to detect the dynamic obstacles in the environment, and individual local path planning algorithms may not always guarantee the existence of the feasible solution for the complex environment. Therefore, a hybrid algorithm which effectively combines global and local path planning is proposed in this paper to overcome these drawbacks. The A* algorithm is used in the global path planning to generate a global path for USV to reach the target point. The dynamic window algorithm (DWA) is used in the local path planning to avoid the dynamic obstacles and track the global path by following the local target point which is the intersection of the global and local path planning. The weight coefficient considering sea state is added in the objective function of DWA, where the security of USV can be guaranteed by reducing the weight of velocity and increasing the weight of distance when the sea state level becomes high. Thus, USV can get a global optimal path and reach the target point in complex environment with dynamic obstacles and ocean currents via the proposed hybrid algorithm, and the comparative simulation is carried out to verify the effectiveness and advantage of the proposed method. INDEX TERMS Hybrid path planning, dynamic window algorithm, unmanned surface vehicles, A* algorithm.

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