Mobile robot autonomous exploration method fusing path information richness

Abstract

The invention discloses a mobile robot autonomous exploration method fusing path information richness, and the method comprises the following steps of: acquiring environmental information in a sensingrange by a robot and changing an environment from an unknown state to a known state; generating a quick search random tree in an idle area of the known state, clustering boundary points of the quicksearch random tree by adopting a clustering algorithm to obtain centroid points, and meanwhile, detecting a grid state of the boundary points and removing invalid points; combining the information gain, the path cost, the path information richness and the boundary point information richness to construct a revenue function, and calculating a revenue value of the revenue function at each centroid point; selecting the centroid point with the maximum income value as a target point, and guiding the robot to move to the target point; and repeating the above steps until the whole environment is explored to obtain a grid map. According to the method, the path information richness and the boundary point information richness are added when the revenue function is constructed, consideration factors in the boundary point selection process are enriched, the perception uncertainty of the robot is reduced, and the exploration efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of autonomous exploration of robots, in particular to an autonomous exploration method of a mobile robot that integrates path information richness. Background technique [0002] The breakthrough of artificial intelligence technology has brought great opportunities to the research of mobile service robots. At present, mobile service robots such as guiding robots, sweeping robots, shopping guide robots, and cargo handling robots have been successfully applied to many places such as airports, supermarkets, museums, and homes. kind of environment. Mobile robot autonomous exploration refers to the process of building a complete environment map by moving in a new environment without any prior knowledge. At present, the main autonomous exploration methods can be roughly divided into two categories: grid map-based exploration methods and feature map-based exploration methods. Among them, the mainstream of the rese...

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Problems solved by technology

However, when the robot chooses the boundary point with the largest profit value at a certain moment to explore and reaches the target point, because the surrounding environment structure exceeds the perception range of the sensor configured by itself, the robot will appear to wander around this point, resulting in perception uncertainty The phenomenon

The existing boundary point information gain model only considers the information gain of the boundary point and the path cost of the exploration process, but does not consider the environmental information of the exploration process, which leads to the robot easily falling into the maximum local revenue function, increasing the uncertainty of robot positioning, and low exploration efficiency , the wandering phenomenon is serious

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