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Continuous Multi-Agent Path Finding for Drone Delivery  ( CPCI-S收录 EI收录)  

文献类型:会议论文

英文题名:Continuous Multi-Agent Path Finding for Drone Delivery

作者:Chen, Ming[1];He, Ning[2];Hong, Chen[3]

通讯作者:He, N[1]

机构:[1]Beijing Union Univ, Beijing Key Lab Informat Serv Engn, Beijing 100101, Peoples R China;[2]Beijing Union Univ, Coll Smart City, Beijing 100101, Peoples R China;[3]Beijing Union Univ, Coll Robot, Beijing 100101, Peoples R China

第一机构:北京联合大学北京市信息服务工程重点实验室

通讯机构:[1]corresponding author), Beijing Union Univ, Coll Smart City, Beijing 100101, Peoples R China.|[11417]北京联合大学;

会议论文集:7th Chinese Conference on Pattern Recognition and Computer Vision

会议日期:OCT 18-20, 2024

会议地点:Urumqi, PEOPLES R CHINA

语种:英文

外文关键词:Drone Delivery; MAPF; RCCBS; Conflict Detection; Conflict Resolution; Continuous Time

摘要:Unmanned Aircraft Systems Traffic Management (UTM) is important for the safety and efficiency of multiple drone delivery. In the paper, we introduce continuous time Multi-Agent Path Finding (MAPF) for UTM system with pre-flight Conflict Detection and Resolution (CDR), and propose a new version of MAPF named Multi-Drone Delivery Path Finding (MDDPF), where agents move continuously in the metric space with different path costs and traverse the conflict-free paths in round trips. We also propose a novel algorithm called RCCBS that continuously solves a continuous-time MAPF instance according to newly assigned tasks. Simulations on the Sendai 2030 drone delivery model case show that RCCBS efficiently solves the MDDPF problem.

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