Inspection robot optimal path dynamic planning method

Abstract

The invention discloses an inspection robot optimal path dynamic planning method which comprises the following steps: forming an undirected graph, generating a deep optimization spanning tree, converting the deep optimization spanning tree into a matrix, searching a leaf node, generating a shortest path fragment set and connecting the path fragment set to generate the shortest path. According to the inspection robot optimal path dynamic planning method, any position in the undirected graph is taken as the starting point to calculate the shortest path, and the inspection path with the shortestlength is obtained to realize the optimal path dynamic planning; in addition, the optimal path has the inspection characteristic of first near then far and conforms to the habit of onsite inspection;and moreover, a charging point is taken as the ending point of the optimal path to ensure that the robot can be charged for endurance.

Description

technical field [0001] The invention belongs to the technical field of robot control, and in particular relates to a dynamic planning method for an optimal path of an inspection robot. Background technique [0002] The existing robot inspection process generally returns to the charging pile after detecting all the detection points, and usually uses the Euler circuit and the traveling salesman problem for path planning. [0003] Euler circuit: If a path in graph G includes each edge exactly once, the path is called Euler path (EulerPath), for two reasons: 1. Whether an undirected graph is an Euler graph is conditional: if and Only if the graph is connected and has no odd-degree vertices. Undirected graphs constructed on site do not necessarily meet this condition, such as tree-structured undirected graphs. 2. The Euler diagram requires that each edge be exactly once, and the robot on site can walk the repeated edge, and it is unavoidable. For example, when the robot walks t...

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Problems solved by technology

Because the condition of the traveling salesman problem also requires each point to be visited once, but the undirected graph constructed on the spot cannot satisfy it, because it may be an undirected graph with a tree structure

[0005] The existing search algorithm can solve the problem of the shortest path, but the inspection process is different from the on-site inspection habit (or human subjective consciousness: first near and then far). For example: the existing 6 generating units are (1F, 2F, 3F, 4F, 5F, 6F), the path generated by the robot using the depth-first algorithm at a certain position on 1F makes the inspection sequence of the robot 6F→5F→4F→3F→2F→1F, and the customer's inspection habits It is 1F→2F→3F→4F→5F→6F

Contrary to the on-site inspection principle: first near and then far

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