| WANG Tengda(王腾达)*,WU Wenjun*,YANG Feng*,SUN Teng**,GAO Qiang*.[J].高技术通讯(英文),2023,29(3):279~287 |
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| A greedy path planning algorithm based on pre-path-planning and real-time-conflict for multiple automated guided vehicles in large-scale outdoor scenarios |
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| DOI：10. 3772/ j. issn. 1006-6748. 2023. 03. 006 |
| 中文关键词: |
| 英文关键词: automated guided vehicle (AGV),multi-agent path finding (MAPF),complex terrain,greedy algorithm |
| 基金项目: |
| Author Name | Affiliation | | WANG Tengda(王腾达)* | (*Faculty of Information Technology,Beijing University of Technology,Beijing 100124,P. R. China)
(**The 54th Research Institute of CETC,Shijiazhuang 050081,P. R. China) | | WU Wenjun* | | | YANG Feng* | | | SUN Teng** | | | GAO Qiang* | |
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| 中文摘要: |
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| 英文摘要: |
| With the wide application of automated guided vehicles (AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path finding (MAPF) algorithm is urgently needed to ensure the efficiency and realizability of the whole system. The complex terrain of outdoor scenarios is fully considered by using different values of passage cost to quantify different terrain types. The objective of the MAPF problem is to minimize the cost of passage while the Manhattan distance of paths and the time of passage are also evaluated for a comprehensive comparison. The pre-path-planning and real-time-conflict based greedy (PRG) algorithm is proposed as the solution. Simulation is conducted and the proposed PRG algorithm is compared with waiting-stop A? and conflict based search (CBS) algorithms. Results show that the PRG algorithm outperforms the waiting-stop A? algorithm in all three performance indicators,and it is more applicable than the CBS algorithm when a large number of AGVs are working collaboratively with frequent collisions. |
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