Multi-node Cooperative Landing Position Planning Method Based on Genetic Particle Swarm Optimization

A particle swarm algorithm and multi-node technology, applied in aerospace deep space exploration, artificial intelligence field

Active Publication Date: 2021-08-20
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, the basic particle swarm optimization algorithm is often used to solve continuous optimization problems, and it is easy to fall into local optimum

Method used

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  • Multi-node Cooperative Landing Position Planning Method Based on Genetic Particle Swarm Optimization
  • Multi-node Cooperative Landing Position Planning Method Based on Genetic Particle Swarm Optimization
  • Multi-node Cooperative Landing Position Planning Method Based on Genetic Particle Swarm Optimization

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Embodiment

[0059] A multi-node collaborative landing position planning method for detectors based on genetic particle swarm optimization, such as figure 1 As shown, the specific implementation process is as follows:

[0060] Step 1: Take the landing zone raster map data obtained by the probe as input. The coordinates (x, y) of each grid point represent the landing point, and the grid map of the detector landing area is abstracted to only distinguish between obstacle areas and non-obstacle areas. The grid map data used in this embodiment is as follows: Figure 6 As shown in , the raster image is a 32×32 matrix, 0 indicates a non-obstacle area, and 1 indicates an obstacle area.

[0061] Step 2: Set the node connection mode of the detector, namely:

[0062]

[0063] Initialize the detector constraint parameters, set the number of nodes n=3, node radius r=2, and the minimum distance between nodes d min = 10, the maximum distance d between nodes with flexible physical connections max =...

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Abstract

The invention discloses a multi-node coordinated landing position planning method for a detector based on a genetic particle swarm algorithm, which belongs to the technical field of aerospace deep space exploration and artificial intelligence technology. According to the method of the invention, aiming at the landing position planning problem of the multi-landing node detector system, the grid map is used to process the landing area map data and obstacle information, the particle swarm algorithm is discretized, the crossover mutation operation in the genetic mechanism is integrated, and the The adaptive genetic factor controls the occurrence probability of mutation operation and enhances the global search ability of the algorithm. The method can effectively deal with the anti-interference constraints and connection constraints of the multi-landing node detector system, generate the detector landing points that satisfy the distance constraints, prevent the collision between the detector nodes and the ground obstacles, and maintain the existence of flexible physical connections. The nodes are evenly distributed to increase the stability and safety of the probe landing.

Description

technical field [0001] The invention relates to a multi-node cooperative landing position planning method for a detector, in particular to a multi-node cooperative landing position planning method for a detector based on a genetic particle swarm algorithm, which belongs to the technical field of aerospace deep space detection and artificial intelligence technology. Background technique [0002] The aerospace field is one of the main fields for the development of autonomous intelligent technology in the 21st century. For deep space exploration missions, the target is generally far away from the earth, the communication delay is large, and the environment is uncertain, which leads to huge challenges in the operation and control of the probe. [0003] Using artificial intelligence technology to improve the on-board autonomy of the probe is a mainstream direction to solve the above-mentioned problems of deep space probes. The landing of the probe is a key stage in the deep spac...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/08G06N3/00G06N3/12
CPCG05D1/0833G06N3/006G06N3/126
Inventor 赵清杰陈涌泉
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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