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Fast 3D path planning method for underwater robot based on goal-oriented centralized optimization

An underwater robot and target-oriented technology, applied in three-dimensional position/channel control, etc., can solve problems such as slow convergence speed, high memory requirements, and low efficiency, so as to reduce randomness, improve convergence rate and path quality, and improve The effect of search efficiency

Active Publication Date: 2020-05-05
HOHAI UNIV
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Problems solved by technology

However, for underwater undulating terrain obstacles and scattered floating obstacles, the RRT* method is optimized through iterative sampling in the entire planning domain, so there are problems of high randomness and low efficiency when searching for nodes, and it is still difficult to solve in large-scale or high-dimensional spaces. There are problems such as slow convergence speed and high memory requirements

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  • Fast 3D path planning method for underwater robot based on goal-oriented centralized optimization
  • Fast 3D path planning method for underwater robot based on goal-oriented centralized optimization
  • Fast 3D path planning method for underwater robot based on goal-oriented centralized optimization

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Embodiment Construction

[0036] In order to clearly highlight the purpose and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings in the examples of the present invention, a fast three-dimensional path planning method for underwater robots disclosed in the embodiments of the present invention , the implementation process mainly includes the following steps:

[0037] (1) Import the environment information, set the start point and end point, create a search tree Tree=(V,E) containing the vertex V and the edge E, at the initial moment, V only contains the start point x start , E is an empty set.

[0038] (2) According to the target point coordinates, use the target-oriented Gaussian sampling strategy to take the Gaussian sampling point x in the planning domain gs and assign to x sample .

[0039] (3) Find the point x closest to the sampling point on the tree nearest , according to the formula

[0040] get new node...

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Abstract

The invention discloses a fast underwater robot three-dimensional path planning method with target-oriented centralized optimization. A target-oriented Gaussian sampling strategy is introduced in an RRT* path planning method, thereby reducing the randomness of sampling points when underwater obstacle distribution is scarce; random disturbance is combined for sampling, a random tree can be reasonably away from an obstacle area, falling into the local minimum is avoided, and search is quickly orientated to the target; and a centralized optimization search strategy is used to perform path optimization processing on the initial path acquired in the invention, the optimization convergence rate and the path quality are improved, and progressive optimization is realized. Compared with the traditional RRT* method, the improved method disclosed in the invention plans a better initial path, the path optimization speed is quicker, and consumption of time and memory is greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of path planning for mobile robots, and relates to a three-dimensional path planning method for an underwater robot. Background technique [0002] Robot underwater navigation is an important application and new development of navigation technology. Path planning is an important link and subject of navigation research. An optimal or sub-optimal path that avoids obstacles. The 3D path planning of underwater robots must find paths through effective methods for underwater terrain obstacles and floating obstacles. At present, the global path planning methods mainly include A * , Ant Colony Algorithm, RRT, etc. A * Relying on heuristic functions, it cannot handle high-dimensional and large-scale problems well. The ant colony algorithm is more likely to fall into a local minimum, making it impossible to plan a feasible path. RRT is more suitable for high-dimensional spaces and nonlinear dynamic environments, ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/10
CPCG05D1/10
Inventor 王慧斌傅笑沈洁张丽丽陈哲
Owner HOHAI UNIV
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