Autonomous obstacle-avoiding planning method of tour detector based on binocular stereo vision

Abstract

An autonomous obstacle-avoiding planning method of a tour detector based on a binocular stereo vision is characterized by: generating DEM data of a local topography; constructing a raster map of a field range of a binocular stereo vision system, carrying out DEM data statistics to each grid in the map and carrying out de-noising processing to the DEM; carrying out topography traversability analysis so as to generate a suitability map; using the suitability maps generated during back and forth two planning to carry out data fusion and obtaining the fused suitability map which is used in the obstacle-avoiding planning; placing several alternative path arcs on the suitability map; evaluating the each alternative path arc from two aspects of a distance from the alternative path arc to a target point and a safe obstacle-avoiding ability; selecting the alternative path arcs whose evaluation values are higher a setting threshold from all the alternative path arcs and selecting the path arc who has the highest evaluation value as a result of the obstacle-avoiding planning. The method of the invention is simple and complete. Security is high. Planning efficiency is high. Engineering realization is easy to be achieved. The method can be used to perform a tour detection task of a complex terrain.

Description

technical field [0001] The invention relates to an autonomous obstacle avoidance planning method, which is suitable for autonomous obstacle avoidance planning of patrol detectors in a type of complex unknown terrain. Background technique [0002] Autonomous obstacle avoidance planning is a branch in the research field of mobile robot path planning. The so-called path planning refers to finding a safe and non-collision movement path for the mobile robot from the starting point to the target point in an environment with obstacles. The research of path planning generally involves two problems of environment description and path search. Among them, environment description refers to how to effectively express the environment in which the robot lives, and establishes an environment model that can be used for planning; path search refers to using an effective method to search for a suitable path from the established environment model. [0003] According to the different degree of...

AI Technical Summary

Problems solved by technology

These planning methods have different shortcomings in application. The environment model established by the Bug algorithm is a binary map, which is too simple to be suitable for planning on rough and complex terrain; the Morphin algorithm only considers the safety of the terrain. The path search is not combined with the position of the target point, and the path planning is not complete. In addition, the method needs to analyze the different headings of the patrol detector, the modeling is complicated, and the efficiency of autonomous obstacle avoidance planning is low.

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