Multi-robot combined target searching method of animal-simulated space cognition

Abstract

The invention provides a multi-robot combined target searching method based on an animal-simulated space cognition technology, comprising the following steps of: (1) firstly, judging whether information is matched successfully or not; (2) establishing a kinematics model and a sensor model of each robot; (3) finishing calibration and matching of inner parameters of a camera; (4) utilizing a self-organization attractor network algorithm model to position the robots; (5) establishing fusion of an environment map and a multi-robot map; (6) navigating and searching a target; and (7) judging whether a task is finished or not; if so, finishing a searching task; otherwise, continually entering the step (2) and repeatedly carrying out a map construction and target searching process. According to the multi-robot combined target searching method, binocular vision can be used for automatically perceiving environmental information under the condition of no any artificial road sign; when the robots navigate and search a target and when the robots enter the same environment, an existing cognition map can be directly called to navigate, so that the working efficiency of the system is greatly improved.

Description

technical field [0001] The invention belongs to the field of positioning and path planning of robots in an unknown environment, is an application combining robot technology and animal space cognition technology, and particularly relates to a multi-robot joint target search method imitating animal space cognition. Background technique [0002] At present, in terms of robot positioning and path planning in an unknown environment, the robot has no reference and can only rely on its own inaccurate sensors to obtain external information, just like a blind person groping in an unfamiliar environment. In this case, positioning is more difficult. Both positioning with a map and creation of a map with positioning are easy to solve, but positioning without a map and creation of a map without positioning are like the "chicken-egg" problem, and there is no way to start. Under such conditions, how to realize multi-robot cooperation and complete target rapid search is a hot spot and also...

AI Technical Summary

Problems solved by technology

[0002] At present, in terms of robot positioning and path planning in an unknown environment, the robot has no reference and can only rely on its own inaccurate sensors to obtain external information, just like a blind person groping in an unfamiliar environment

In this case, positioning is more difficult

Both positioning with a map and creation of a map with positioning are easy to solve, but positioning without a map and creation of a map with unresolved positioning are like the "chicken-egg" problem, and there is no way to start

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