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

Abstract

A storage robot path program method based on linear temporal logic theory comprises the steps of modeling a storage environment into a weight switching system based on assignment nodes; describing complex assignment tasks of the storage system by using the linear temporal logic language (LTL); then, switching the task formula into a Buchi automatic machine through an LTL2BA tool kit; conducting cartesian product to the extensible weight switching system and the Buchi automatic machine to form a task feasible network topology; employing SPFA(Shortest Path Faster Algorithm) on the topology to search an optimal path, wherein the task feasible network topology includes storage environment information and package-taking task information, guaranteeing that the searched obtained path is the optimal path and isn't influenced by the order of the selected assignment node; mapping the obtained optimal path from the task feasible network topology to the corresponding optimal path in the storage environment, and sending the optimal path to a storage robot by radio communication through a PC to finish the packaging-taking and assignment task.

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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