Beijing Institute of Technology

Sai Lu

Qing Bo Wang

Bin Xin

Jie Chen

Miao Wang

Fang Deng

Jiwei He

Lihua Dou

Mengjie Jing

Yingmei He

A multi-robot collaboration method in a flexible hardware production workshop is provided, by which allocation of workpiece machining tasks and transfer of workpieces in different workstations can be achieved and meanwhile relatively high calculation cost is avoided. According to the method, a distributed collaboration method is fully used, and in allusion to the current technical condition, the allocation of the workpiece machining tasks and the transfer of the workpieces in different workstations can be achieved and meanwhile the relatively high calculation cost is avoided. A multi-AGV path conflict eliminating method is used for avoiding possible collision of AGVs during movement. A centralized intervention and adjustment method is used for discovering and predicting system conflicts and failure problems and making timely dispatching and adjustment so as to improve the automation level and the flexibility level of a hardware workshop.

Multi-machining robot collaboration method in flexible hardware production workshop

Disclosed is a large-scale dynamic double-effect scheduling method for a flexible job shop based on genetic programming (GP). In a GP implementation process of the present disclosure, in addition to features related to workpieces, processing robots and automated guided vehicles (AGVs), such as processing time of working procedures and buffer area waiting time, features of a ratio of processing time to transfer time and a ratio of processing energy consumption to transfer energy consumption are also added in a terminal set to cause job shop environment features to be more comprehensively applied to a scheduling rule design, thereby automatically designing a more consistent and accurate scheduling rule. A double-effect scheduling rule of the present disclosure overcomes the shortcomings of slow convergence speed, difficulty in rapid corresponding changes and unfit scheduling rules, and can quickly produce a more efficient and energy-saving production scheduling scheme.

Large-scale dynamic double-effect scheduling method for flexible job shop based on genetic programming

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Beijing, China

Sai Lu