Multi-stage optimized unmanned ship path planning method and device
A path planning and ship technology, applied in the field of multi-level optimized unmanned ship path planning method and device, can solve problems such as falling into local extreme values, difficult to apply intelligent ship path planning, and reduced calculation amount
Active Publication Date: 2020-08-21
智慧航海(青岛)科技有限公司
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It can be seen that the beetle whisker search algorithm only needs to propose one algorithm individual to search, and the amount of calculation is greatly reduced. However, in the actual process, the beetle individual only perceives the direction of the next position at the current position, and it is easy to fall into a local extremum, which is difficult to apply In the path planning of intelligent ships
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[0061] In order to better explain the present invention and facilitate understanding, the present invention will be described in detail below through specific embodiments in conjunction with the accompanying drawings.
[0062] The multi-level optimized unmanned ship path planning method and path planning device proposed in the embodiment of the present invention, by integrating the annealing process of the simulated annealing algorithm into the beetle whisker search algorithm to carry out path planning, greatly reduces the amount of calculation, and avoids the path In the planning, the beetle's whisker algorithm falls into a local optimal problem, so that it can plan an economical and safe navigation path.
[0063] In order to better understand the above technical solutions, the following will describe exemplary embodiments of the present invention in more detail with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in t...
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The invention relates to a multi-stage optimized unmanned ship path planning method. The method comprises the following steps of: based on the self information, navigation environment information andnavigation task information of a target ship, performing path planning by adopting a longicorn algorithm, in the path planning process, if the smell concentration increment of a next position of longicorn relative to a current position of the longicorn is greater than zero, calculating the acceptance probability of the next position of the longicorn, if the acceptance probability is greater than apreset threshold, taking the next position of the longicorn as the current position of the longicorn, otherwise, abandoning the next position of the longicorn, and if the current iteration frequencyis greater than the maximum iteration frequency, reducing the temperature of simulated annealing, continuing to search the path when the temperature is greater than the minimum temperature, and outputting the planned path when the temperature is less than the preset minimum temperature; and controlling the ship to sail according to the planned path by the target ship. The calculation amount is greatly reduced, and the problem that the longicorn beard algorithm is caught in local optimum in path planning is avoided. The invention further provides a multi-stage optimized unmanned ship path planning device.
Description
technical field [0001] The invention relates to the technical field of intelligent ship path planning, in particular to a multi-level optimized unmanned ship path planning method and device. Background technique [0002] Intelligent ship path planning is the primary technology to realize the autonomous navigation of the ship. Specifically, the navigation environment model is constructed based on the electronic chart information and the environmental information perceived by the ship, and then the autonomous path planning is carried out based on the navigation environment model and navigation tasks. Based on the actual operation of smart ships, the path planning algorithm is required to be highly efficient, and can achieve optimal results, and finally obtain a safe and economical navigation route. [0003] At present, common path planning algorithms are mainly divided into two categories: graph search-based and intelligent optimization algorithms, among which path planning ba...
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Login to View More IPC IPC(8): G05D1/02
CPCG05D1/0206Y02T10/40
Inventor王晓原夏媛媛姜雨函高杰柴垒孙正濮朱慎超
Owner智慧航海(青岛)科技有限公司