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A multi-agent formation planning method based on local vision

A multi-agent, intelligent body technology, applied in two-dimensional position/channel control, instrument, control/regulation system, etc., to achieve the effects of good stability, reduced calculation difficulty, and simple calculation

Active Publication Date: 2021-12-28
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0011] At present, there is no formation planning method that can solve the above problems at the same time, so as to better realize the practical application of the multi-agent formation planning method

Method used

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  • A multi-agent formation planning method based on local vision
  • A multi-agent formation planning method based on local vision
  • A multi-agent formation planning method based on local vision

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Embodiment Construction

[0119] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention, and the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0120] The present invention adopts a set of layered reinforcement learning structure to separate the influence of each sub-task on each other during training. Specifically, we split the overall task into two sub-strategies and a high-level strategy. The two sub-strategies are the path planning strategy and the formation maintenance strategy. The path planning strategy is only responsible for planning the collision-free trajectory from the multi-agent to...

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Abstract

The present invention relates to a multi-agent formation planning method based on local vision, comprising the following steps: Step S3: Step S4 and Step S5 are run for the first agent; Step S4: The agent performs local observation on the environment to obtain the local observation value; step S5: input the local observation value obtained in step S4 into the agent, and the agent outputs the action of the current time step after the calculation of the pre-trained high-level policy reinforcement learning algorithm model; step S6: for the second to N agents run steps S4 and S5; step S7: repeat steps S3 to S6 until the target task is completed; using the multi-agent formation planning method based on local vision, the agents only rely on the limited observation space around them to make decisions, It gets rid of the shortcoming that the centralized planning method must rely on global information, so that the method can be used for formation planning of multiple agents on a large-scale map.

Description

technical field [0001] The invention belongs to the field of multi-agents, and in particular relates to a multi-agent formation planning method based on a local vision. Background technique [0002] Multi-agents have been deployed in many real-world applications, including drone swarms, aircraft tugs, and warehouse robots. In many cases, it is important for an agent to find its way while avoiding obstacles while maintaining a specific formation. For example, when warehouse robots need to transport large goods together. However, current multi-agent path planning algorithms cannot simultaneously plan and maintain formation in this situation, because most of them do not consider the formation factor. [0003] At present, there are very few path planning algorithms that focus on solving the problem of multi-agent formation planning. Multi-agent formation planning, a variant of multi-agent path planning, consists of two key subtasks: planning multiple conflict-free paths while...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02
CPCG05D1/0217G05D1/0287G05D2201/0216
Inventor 刘勇刘善琪
Owner ZHEJIANG UNIV
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