Search algorithm and verification method for swarm robots based on physarum polycephalum foraging

Abstract

The invention relates to the technical field of multi-agent genetic algorithms, in particular to a search algorithm and a verification method for swarm robots based on physarum polycephalum foraging. The swarm robots are divided into three types of robots which are named as CORE, BRANCH and FORAGER; operation processing steps of data comprise four phases, namely an initialization phase, a dispersion search phase, an edge search phase and a signal source attracting phase. According to the search algorithm and the verification method disclosed by the invention, search calculation is performed by adopting a mode of controlling the swarm robots to execute simulation of the physarum polycephalum foraging by pseudocodes; simulated experiment verification for a single signal source and multiple signal sources is realized by a simulation experiment platform; demonstration and verification of the single signal source are realized in a hardware simulation experiment, and thus better effects and conclusions for coverage search in a situation of limited communication radius of the robot are obtained by the algorithm disclosed by the invention, and a simple algorithm which less depends on robot communication and adapts to area coverage searching is realized; the algorithm has higher efficiency and application value for the area coverage searching.

Description

technical field [0001] The invention relates to the technical field of swarm intelligence algorithms, especially a bionic search algorithm for simulating the foraging process of a slime mold group, and more specifically, a search algorithm based on the foraging of Phytophthora polycephala that completes the search through the local interaction of group robots. Swarm robot search algorithm and verification method. Background technique [0002] The so-called area coverage search refers to the process that a robot carrying a sensor with a certain detection range (such as laser, sonar, etc.) explores and visits the entire area and completes the corresponding task. This has been one of the challenging frontiers in research. In recent years, with the needs of practical applications and the continuous deepening of robot research, the research on area coverage search has attracted the attention of many scholars. The use of swarm robots to complete area coverage search tasks has th...

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Problems solved by technology

[0007] Regarding the research on area coverage search using swarm robots, although the Chinese patent No. 201610749188.9 discloses a hybrid search method for swarm robots based on biological foraging behavior, this method uses swarm robots to search for targets and promotes the search for swarm robots. The organization principle and the emergence of cooperative behavior are based on the mixed search method of swarm robots based on biological foraging behavior. The grid method is used to model the search environment, the search area is divided into several sub-areas, the search order of each sub-area is arranged, and the mixed search Although the patent uses robots to replace humans to complete many tasks, such as mine clearance, space exploration, survivor search after earthquakes and other disasters, mine disaster search and rescue, etc., the algorithm is relatively complicated, and the execution time is relatively long and accurate The patent No. 201510481231.3 discloses a multi-robot group task search and task execution method. According to the different forms of tasks and the different forms of robot cooperation, the multi-robot collaboration is also divided into the following three forms. : Multi-robot sequential collaboration, multi-robot synchronous collaboration, multi-robot free collaboration, although this invention can be applied to perform more complex tasks, and decompose complex tasks into several parts, but the execution time is relatively long, the program is relatively complicated, and it is easy to crash

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