Energy-saving underwater path planning method based on reexcitation mechanism particle swarm optimization

A particle swarm algorithm and path planning technology, applied in control/regulation systems, non-electric variable control, height or depth control, etc., and can solve problems such as being easily affected by ocean currents

Active Publication Date: 2021-07-30
HOHAI UNIV
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Purpose of the invention: Aiming at the current technical problems that AUVs are easily affected by ocean currents when working in complex ocean environments, and the power consumption of underwater robots needs to be considered, this invention proposes an energy-saving underwater path based on the particle swarm algorithm of the re-excitation mechanism The planning method is to use the speed synthesis method to offset the negative influence of the ocean current and make full use of the ocean current, thereby saving the energy of the AUV; at the same time, in order to improve the adaptive ability of the particle swarm algorithm, the underwater improved particle swarm algorithm based on the re-excitation mechanism is used. Then plan an optimal path

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Energy-saving underwater path planning method based on reexcitation mechanism particle swarm optimization
  • Energy-saving underwater path planning method based on reexcitation mechanism particle swarm optimization
  • Energy-saving underwater path planning method based on reexcitation mechanism particle swarm optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0059] Such as figure 1 As shown, the present invention is based on the energy-saving underwater path planning method of the re-excitation mechanism particle swarm algorithm, uses the Graham algorithm and the MAKLINK graph theory to carry out environmental modeling, uses the Dijkstra algorithm to carry out path sub-optimization, and uses the improved particle swarm algorithm to carry out path finalization. Optimization, and in order to reduce the number of robot corners, use Bezier curves to smooth the path.

[0060] The underwater path planning method based on the particle swarm algorithm of the re-excitation mechanism of the present invention comprises the following steps:

[0061] In step (1), a convex polygonal obstacle model is established according to the Graham algorithm, and a set distance is expanded outward to establish a danger zone. The specific process is as follows:

[0062] Step (1.1), such as figure 2 As shown, design a random number of points P on the two-d...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an energy-saving underwater path planning method based on a reexcitation mechanism particle swarm algorithm, and the method comprises the steps: firstly generating a convex polygon obstacle through a Graham algorithm, and enabling the obstacle to expand outwards to generate a danger region; then, using an MAKLINK graph theory method to connect vertex lines of the convex polygon obstacle to generate an undirected network graph; carrying out preliminary suboptimal path planning by utilizing a Dijkstra algorithm to obtain a shortest link line; improving a particle swarm algorithm by using a reexcitation mechanism, and fusing the particle swarm algorithm into the influence of the ocean current, so that the autonomous underwater vehicle (AUV) is ensured to utilize the ocean current to the maximum extent, and energy is saved; and then performing path optimization by using the final improved particle swarm algorithm, and smoothing the optimal path by using the Bessel algorithm, so that the optimal path is found under the condition that the AUV saves energy, and safe obstacle avoidance is realized.

Description

technical field [0001] The invention relates to a path planning method for an underwater robot, in particular to an energy-saving underwater path planning method based on a re-excitation mechanism particle swarm algorithm. Background technique [0002] AUV is the main tool for humans to explore the ocean. When interacting with the external environment underwater, it is crucial to safely avoid obstacles and plan a reasonable path to ensure the safety of underwater robots. The underwater environment is complex and has various obstacles. Among them, AUV is most affected by ocean currents. Therefore, considering ocean currents in underwater path planning is of great significance for saving robot energy. [0003] At present, there are many researches on the path planning of underwater robots in the two-dimensional environment, such as the typical A* algorithm, the ant colony algorithm (Ant Colony Algorithm, ACO), the artificial potential field method (Artificial Potential Field M...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G05D1/06
CPCG05D1/0692
Inventor 黄浩乾金超吴昊李光辉魏嘉颖杨晨
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products