Tight coupling task allocation method based on improved ant colony algorithm

A technology of task allocation and ant colony algorithm, applied in the direction of calculation, calculation model, instrument, etc., can solve the problems of reasonable model difficulty, the initial solution of ants is not superior, and the convergence speed is slow.

Pending Publication Date: 2021-03-02
HARBIN ENG UNIV
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Problems solved by technology

It often leads to the initial solution of ants not having superiority, so it will lead to a long search time
[0006] (2) In multi-robot task assignment, it is difficult to establish a reasonable model for problem solving. When mapping the actual problem to the activities of individual ants, it often leads to an increase in the search time of the ants, resulting in a slower convergence speed when solving the problem.

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  • Tight coupling task allocation method based on improved ant colony algorithm
  • Tight coupling task allocation method based on improved ant colony algorithm
  • Tight coupling task allocation method based on improved ant colony algorithm

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Embodiment 1

[0072] Tightly coupled tasks refer to tasks that require the cooperation of multiple robots. There is no timing and binding relationship between tasks, and collaboration requires robot alliances. At present, in the assignment of tightly coupled tasks, the most important thing is to select a suitable robot alliance to generate an alliance solution by means of permutation and combination plus algorithm screening, and to find the optimal solution through a certain strategy. The generation of the alliance solution mainly considers two factors: the first is whether the robot alliance can successfully perform the task and match the task.

[0073] In the actual study of a multi-robot system, each robot is heterogeneous, so the corresponding capabilities of each robot are different, so the robot capabilities must be expressed mathematically. In the environment, the types of robot abilities must be limited, and these existing abilities are called basic abilities, and the agent's abilit...

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Abstract

The invention belongs to the technical field of robot task allocation, and particularly relates to a tight coupling task allocation method based on an improved ant colony algorithm. Aiming at the problems of the ant colony algorithm in the field of multi-robot task allocation at the present stage, a strategy of searching robots from tasks by ants is adopted, and a reference set is provided for updating pheromones of the ant colony algorithm in combination with a random search algorithm, so that the convergence speed is increased, and the task allocation solving accuracy is improved. Accordingto the method, the random search algorithm is introduced into the traditional ant colony algorithm, so that the early-stage convergence speed of the traditional ant colony algorithm is increased, thesituation that the traditional ant colony algorithm is prone to falling into local optimum is optimized, multi-robot task allocation is effectively achieved, and the defects that the traditional ant colony algorithm is slow in convergence, prone to falling into local optimum and the like are well overcome.

Description

technical field [0001] The invention belongs to the technical field of robot task assignment, and in particular relates to a tightly coupled task assignment method based on an improved ant colony algorithm. Background technique [0002] Since entering the 21st century, with the rapid development of science and technology, robots can work in different complex or uncertain environments, and have been widely used to perform various military tasks, including surveillance, reconnaissance, attack and damage assessment, etc. However, due to certain constraints such as resources, this makes it difficult for a single robot to complete complex multi-objective large-scale tasks alone. Therefore, multi-robot systems have gradually attracted the attention of researchers. Compared with a single robot, a multi-robot system has superior distribution characteristics, including time, space, function, resources, and information. In addition, the excellent advantages of multi-robot systems ar...

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Application Information

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IPC IPC(8): G06N3/00G06Q10/06
CPCG06N3/006G06Q10/06312G06Q10/06311
Inventor 张子迎王浩徐东孟宇龙陈玉炜高荣彬
Owner HARBIN ENG UNIV
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