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Autonomous Last-Mile Delivery Based on the Cooperation of Multiple Heterogeneous Unmanned Ground Vehicles
Author(s) -
Yuzhan Wu,
Yuanhao Ding,
Susheng Ding,
Yvon Savaria,
Meng Li
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/5546581
Subject(s) - last mile (transportation) , computer science , robot , schedule , payload (computing) , task (project management) , heuristic , job shop scheduling , real time computing , mathematical optimization , distributed computing , engineering , mile , computer network , artificial intelligence , mathematics , systems engineering , physics , astronomy , network packet , operating system
With the development of e-commerce, the last-mile delivery has become a significant part of customers’ shopping experience. In this paper, an autonomous last-mile delivery method using multiple unmanned ground vehicles is investigated. Being a smart logistics service, it provides a promising solution to reduce the delivery cost, improve efficiency, and avoid the spread of airborne diseases, such as SARS and COVID-19. By using a cooperation strategy with multiple heterogeneous robots, contactless parcel delivery can be carried out within apartment complexes efficiently. In this paper, the last-mile delivery with heterogeneous UGVs is formulated as an optimization problem aimed at minimizing the maximum makespan to complete all tasks. Then, a heuristic algorithm combining the Floyd’s algorithm and PSO algorithm is proposed for task assignment and path planning. This algorithm is further realized in a distributed scheme, with all robots in a swarm working together to obtain the best task schedule. A good solution with an optimized makespan is achieved by considering the constraints of various robots in terms of speed and payload. Simulations and experiments are carried out and the obtained results confirm the validity and applicability of the developed approaches.

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