Task allocation and path planning for multi-robot systems in intelligent warehousing
Faced with today's increasingly complex market demands, traditional manual warehouse systems are becoming inadequate, necessitating the urgent intelligent transformation and upgrading of warehouse systems. In this context, this paper aims to design a task allocation and path planning strategy f...
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EDP Sciences
2024-10-01
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| Series: | Xibei Gongye Daxue Xuebao |
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| Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2024/05/jnwpu2024425p929/jnwpu2024425p929.html |
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| _version_ | 1846125793902592000 |
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| author | CHU Jing TIAN Yiqiu YUE Qi HUANG Yong |
| author_facet | CHU Jing TIAN Yiqiu YUE Qi HUANG Yong |
| author_sort | CHU Jing |
| collection | DOAJ |
| description | Faced with today's increasingly complex market demands, traditional manual warehouse systems are becoming inadequate, necessitating the urgent intelligent transformation and upgrading of warehouse systems. In this context, this paper aims to design a task allocation and path planning strategy for a multi-robot warehouse system to efficiently accomplish mixed single-robot and multi-robot types of warehouse tasks. The study proposes a warehouse task allocation strategy that incorporates traffic flow impact factors into the auction algorithm, optimizing task allocation by predicting robot density in various areas of the environment. For multi-robot formation tasks, a three-robot formation model based on the virtual structure method is designed. Additionally, a two-layer path planning strategy is proposed: the outer layer conducts global path planning based on the Floyd algorithm, while the inner layer resolves various collision issues through traffic rule constraints, achieving local optimal path planning. Simulation experiments conducted on the MATLAB platform show that the multi-robot system can flexibly handle mixed types of warehouse tasks, effectively reducing collision risks between robots and stagnation in dense areas, thereby improving the safety and efficiency of the multi-robot system. This study provides a reference for future research and practical applications of multi-robot systems. |
| format | Article |
| id | doaj-art-d8c234e4f5ac451b8ca932170e6e94a5 |
| institution | Kabale University |
| issn | 1000-2758 2609-7125 |
| language | zho |
| publishDate | 2024-10-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj-art-d8c234e4f5ac451b8ca932170e6e94a52024-12-13T10:05:05ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252024-10-0142592993810.1051/jnwpu/20244250929jnwpu2024425p929Task allocation and path planning for multi-robot systems in intelligent warehousingCHU Jing0TIAN Yiqiu1YUE Qi2HUANG Yong3School of Automation, Xi'an University of Posts and TelecommunicationsSchool of Automation, Xi'an University of Posts and TelecommunicationsSchool of Automation, Xi'an University of Posts and TelecommunicationsSchool of Astronautics, Northwestern Polytechnical UniversityFaced with today's increasingly complex market demands, traditional manual warehouse systems are becoming inadequate, necessitating the urgent intelligent transformation and upgrading of warehouse systems. In this context, this paper aims to design a task allocation and path planning strategy for a multi-robot warehouse system to efficiently accomplish mixed single-robot and multi-robot types of warehouse tasks. The study proposes a warehouse task allocation strategy that incorporates traffic flow impact factors into the auction algorithm, optimizing task allocation by predicting robot density in various areas of the environment. For multi-robot formation tasks, a three-robot formation model based on the virtual structure method is designed. Additionally, a two-layer path planning strategy is proposed: the outer layer conducts global path planning based on the Floyd algorithm, while the inner layer resolves various collision issues through traffic rule constraints, achieving local optimal path planning. Simulation experiments conducted on the MATLAB platform show that the multi-robot system can flexibly handle mixed types of warehouse tasks, effectively reducing collision risks between robots and stagnation in dense areas, thereby improving the safety and efficiency of the multi-robot system. This study provides a reference for future research and practical applications of multi-robot systems.https://www.jnwpu.org/articles/jnwpu/full_html/2024/05/jnwpu2024425p929/jnwpu2024425p929.html仓储系统多机器人系统任务分配路径规划多机器人协同 |
| spellingShingle | CHU Jing TIAN Yiqiu YUE Qi HUANG Yong Task allocation and path planning for multi-robot systems in intelligent warehousing Xibei Gongye Daxue Xuebao 仓储系统 多机器人系统 任务分配 路径规划 多机器人协同 |
| title | Task allocation and path planning for multi-robot systems in intelligent warehousing |
| title_full | Task allocation and path planning for multi-robot systems in intelligent warehousing |
| title_fullStr | Task allocation and path planning for multi-robot systems in intelligent warehousing |
| title_full_unstemmed | Task allocation and path planning for multi-robot systems in intelligent warehousing |
| title_short | Task allocation and path planning for multi-robot systems in intelligent warehousing |
| title_sort | task allocation and path planning for multi robot systems in intelligent warehousing |
| topic | 仓储系统 多机器人系统 任务分配 路径规划 多机器人协同 |
| url | https://www.jnwpu.org/articles/jnwpu/full_html/2024/05/jnwpu2024425p929/jnwpu2024425p929.html |
| work_keys_str_mv | AT chujing taskallocationandpathplanningformultirobotsystemsinintelligentwarehousing AT tianyiqiu taskallocationandpathplanningformultirobotsystemsinintelligentwarehousing AT yueqi taskallocationandpathplanningformultirobotsystemsinintelligentwarehousing AT huangyong taskallocationandpathplanningformultirobotsystemsinintelligentwarehousing |