Shortest Path Planning Method Based on Turn Weight Constraints

Abstract

The invention provides a shortest path planning method based on turning weight constraints. The method includes: step 1, calculate the distance between the source point v and all other nodes, and store the distance between the source point v and all other nodes in the node distance data table; step 2, from U Select a node k with the shortest distance to the source point v, and add k to S; step 3, take node k as the intermediate node, recalculate the distance from each node in U to the source point v based on the turning weight, and recalculate The calculated distance between the source point v and all other nodes is updated and stored in the node distance data table; step 4, repeat steps 2 and 3 until the end point w is added to S, and the source point v to the end point w is obtained the shortest path of . While effectively calculating the shortest path, the present invention carries out weight penalty on turning at the intersection, and the obtained shortest path can avoid turning as much as possible on the basis of short road length, and helps the AGV guide vehicle process to complete the task effectively and quickly.

Description

technical field [0001] The invention relates to the technical field of path planning, in particular to a shortest path planning method based on turning weight constraints. Background technique [0002] AGV (Automated Guided Vehicle) refers to a transport vehicle equipped with automatic guidance devices such as electromagnetic or optical, controlled by a computer, characterized by wheeled movement, and capable of automatically driving along a prescribed guiding path. In intelligent automation service applications such as intelligent parking services or intelligent warehousing, AGV is the main force of transportation, and its omnidirectionality solves the problem of difficult turning of vehicles and realizes 360° any direction driving. [0003] The shortest path planning of AGV in the smart scene needs to follow the current basic domestic traffic rules, including but not limited to left-hand drive, right-hand drive, courteous turning and straight driving, etc., and also needs ...

AI Technical Summary

Problems solved by technology

[0012] The disadvantages of the optimization algorithm for calculating the parking path using the Dijsktra algorithm in the above-mentioned prior art are: the application scenario is generally a warehousing logistics distribution or a large-scale parking lot for man-made parking tasks, so the weight of the algorithm usually only considers the length of the road

For the AGV automatic guidance device of the smart parking lot, it will occupy the opposite lane when turning at the intersection. Therefore, if the shortest path result contains too many turns, it may cause other AGV vehicles to wait or the intersection to be blocked, resulting in delays in vehicle access.

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