Indoor environment robot exploration method and system based on prior information heuristic

Abstract

The invention relates to an indoor environment robot exploration method and system based on a priori information heuristic, comprising the following steps: the robot collects data of surrounding environment information through sensors carried by itself; and based on the data of the surrounding environment information, a part of the map is updated to be a known area , obtain the updated map; use two fast search random trees to extract the boundary of the updated map to obtain the RRT boundary point; identify the heuristic object and perform position estimation on it, and construct the prior based on the position of the heuristic object area, extract boundary points in the prior area, and obtain room boundary points; based on RRT boundary points and room boundary points, the robot explores the indoor environment. It prioritizes exploring the environment in the prior area, allowing the robot to first explore a room area before turning to other areas, effectively reducing the backtracking phenomenon during the exploration process and improving the exploration efficiency.

Description

technical field [0001] The invention relates to the technical field of robot exploration, in particular to an indoor environment robot exploration method and system based on a priori information heuristic. Background technique [0002] The breakthrough of artificial intelligence technology has brought huge opportunities to the research of mobile service robots. The application scenarios and service models of intelligent public service robots continue to expand, driving the rapid growth of my country's service robot market. Autonomous exploration of mobile robots refers to the process that robots build 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 method based on the grid map has rich representation information and high resolution, which is conduci...

AI Technical Summary

Problems solved by technology

Obviously, the second action is more time-consuming and less efficient; the first action of continuing to explore has a greater expected return value

However, current robot exploration strategies evaluate candidate boundary points independently, ignoring the potential benefits of the environment structure, so the backtracking phenomenon of exploration strategies like the second action often occurs

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