Abstract
AbstractWith the high development of online commerce, drone delivery has shown a potential to reduce logistical costs. Multiple drone delivery can be formulated as a multiagent path finding (MAPF) problem which is used to identify a group of collision-free paths for multiple agents. However, most prior work on MAPF has studied on grid graphs, which is not proper for drone delivery problem. We study here a non-grid MAPF problem for drone delivery. Some algorithms for solving grid MAPF can also be applied to this new problem, which can be categorized into two types: search-based methods and dynamic programming methods. However, the challenges created by non-grid features, such as a large state/action space, impede the application of either of these two methods. We therefore propose a novel approach that combines a search method and a dynamic programming method which can accelerate the learning process. The experimental results show our proposed method to be more effective than some existing algorithms.KeywordsMultiagent path findingDrone deliveryMultiagent reinforcement learning
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.