Path Planning Method for Warehousing Robot Based on Linear Sequential Logic Theory

Abstract

The warehousing robot path planning method based on linear temporal logic theory includes: modeling the warehousing environment as a weighted switching system that is scalable based on dispatch nodes; using linear temporal logic language (LTL) to describe the complex dispatch tasks of the warehousing system; then, The task formula is converted into a Büchi automaton through the LTL2BA toolkit; the Cartesian product of the scalable weighted switching system and the Büchi automaton is used to form a feasible network topology for the task; the SPFA (Shortest Path Faster Algorithm) algorithm is used on this topology to search for the optimal path , the task feasibility network topology includes warehousing environment information and pickup task information. The path obtained by searching can be guaranteed to be the optimal path and is not affected by the selected order of dispatching single nodes; map the optimal path obtained on the task feasibility network topology back to the warehousing environment The corresponding optimal path is sent to the warehousing robot through wireless communication through the PC to complete the task of picking up and dispatching orders.

Description

technical field [0001] The invention relates to a path planning method for a warehousing and logistics mobile robot. Aiming at the specific warehousing environment and picking task requirements, a warehousing robot path planning method based on linear temporal logic theory (LTL) is adopted, and the path planning method can not only meet the task requirements, but also meet the requirements of the tasks. The optimal path of environmental information to ensure that warehousing robots can efficiently complete specified tasks and achieve the goal of robots replacing humans, thereby improving work efficiency. Background technique [0002] Due to the rapid development of e-commerce, the application of automation equipment in the field of warehousing and logistics is becoming more and more extensive, and the application of warehousing and logistics robots can greatly improve the efficiency of e-commerce warehousing and logistics work, and alleviate the current shortage of supply in ...

AI Technical Summary

Problems solved by technology

The genetic algorithm starts searching from the string set of problem solutions instead of starting from a single solution, and processes multiple individuals in the group at the same time, which can effectively avoid the risk of the traditional optimization algorithm iteratively seeking the optimal solution from a single initial value and falling into a local optimal solution , but the efficiency of genetic algorithm is usually lower than its traditional optimization method, and its evolution process takes up a lot of computing time and memory space

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