Polyclonal artificial immune network algorithm for multi-robot dynamic path planning

Abstract

The invention provides a polyclone artificial immunity network algorithm for multirobot dynamic path planning, and relates to an improved polyclone artificial immunity network algorithm. According to the polyclone artificial immunity network algorithm, a polyclone artificial immunity network is applied to multiple mobile robot dynamic path planning, mutual influence among robots and influence on the robots of mobile barriers are considered, a computational formula of antibody concentration is defined, diversity of antibodies is increased through clonal operators, crossover operators, mutation operators and selection operators, and the problem of premature convergence of a traditional immune network is solved. Specific antibodies corresponding to antigens in a specific environment are stored, initial concentration of the specific antibodies is increased, response time is shortened, and multiple mobile robot dynamic path planning in an unknown environment is effectively achieved.

Description

technical field [0001] The invention relates to a polyclonal artificial immune network algorithm applied to dynamic path planning of multiple mobile robots, belonging to the technical field of artificial intelligence. Background technique [0002] The path planning problem is one of the key technologies in the research of mobile robots. Path planning refers to the search of an optimal or suboptimal collision-free path from the starting position to the target position by the mobile robot according to a certain performance index. [0003] According to whether the robot can obtain all environmental information in advance, the path planning of mobile robots can be divided into global path planning with known environmental information and local path planning based on sensor information. Traditional global path planning is mostly based on graph theory. Search for the optimal or suboptimal collision avoidance path that satisfies a certain performance index. The local path planning...

AI Technical Summary

Problems solved by technology

[0010] Aiming at the premature convergence problem of the traditional artificial immune network algorithm in the application of mobile robot path planning in an unknown environment, the present invention proposes a polyclonal artificial immune network algorithm for multi-robot dynamic path planning that can solve the premature convergence problem. Applying the polyclonal artificial immune network to the dynamic path planning problem of multiple mobile robots, considering the interaction between robots and the influence of moving obstacles on the robot, the calculation formula of antibody concentration is defined, through cloning operator, crossover operator, mutation Operators and selection operators increase the diversity of antibodies and solve the premature convergence problem of traditional artificial immune networks; and by introducing memory units, not only the specific antibodies corresponding to specific environmental antigens are preserved, but also the specific antibodies are increased. The initial concentration reduces the response time and effectively realizes the dynamic path planning of multiple mobile robots in an unknown environment

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