Multi-robot rapid task scheduling method based on multi-core computing

Abstract

The invention discloses a multi-robot rapid task scheduling method based on multi-core computing. The method comprises the following steps: modeling a multi-robot system by adopting a Petri network modeling method; converting the Petri net model into a program input file according to a self-defined file format; solving a WOT matrix and a WRT matrix of the Petri network to realize a heuristic function required by the A * search algorithm; constructing an initial identifier, a target identifier, a library operation time vector, a front incidence matrix and a rear incidence matrix of a Petri network system according to the input file; constructing a Treap data structure representation open list supporting concurrency and a binary balance tree data structure representation closed list supporting concurrency; setting the maximum number k of parallel expansion nodes and the number p of parallel computing threads of each round of iteration of the parallel A * algorithm; and running a parallelA * algorithm to search a transmission transition sequence from the initial node to the target node in parallel to obtain a task scheduling scheme. The method has the advantages of strong algorithm parallelism, high parallelism efficiency, high path search efficiency, high quality of the obtained task scheduling scheme and the like.

Description

technical field [0001] The invention belongs to the technical field of multi-robot collaborative system scheduling, in particular to a multi-robot fast task scheduling method based on multi-core computing. Background technique [0002] Multi-robot collaborative system is a task scheduling system with multiple robots, multiple available resources and multiple tasks. The multi-robot system task scheduling problem refers to assigning a group of tasks to several robots to complete. Each robot needs to complete several operations to complete the task. Each operation has several optional operations. The time required for each optional operation to complete It is fixed. The completion of each optional operation requires several resources. Each resource can only be used by one robot at the same time. The goal is to find a task scheduling scheme so that all tasks can be completed in the shortest time. An efficient task scheduling method can shorten the task completion time and great...

AI Technical Summary

Problems solved by technology

[0003] In order to obtain the multi-robot system task scheduling scheme, the traditional method is a scheduling optimization strategy based on the A* search algorithm. First, the data structure used to represent the open list is a sorted linked list, and the data structure used to represent the closed list is a linked list or a set. , so when you want to query the same identification node in the open list or closed list, you must traverse the entire table, resulting in high time complexity and low algorithm implementation efficiency; secondly, although the A* algorithm is the shortest solution in a static road network The most effective direct search method for the path, but with the increase in the size of the Petri network or the increase in the number of initial token tokens, the number of nodes in the reachability graph tends to increase exponentially. At this time, the A* algorithm is used to find the optimal Scheduling still takes a lot of time

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