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|Title:||Development of distributed consensus protocol for multi-unmanned aerial vehicle coordination||Authors:||Tan, Seet Ynn||Keywords:||Engineering::Computer science and engineering::Information systems::Information storage and retrieval||Issue Date:||2022||Publisher:||Nanyang Technological University||Source:||Tan, S. Y. (2022). Development of distributed consensus protocol for multi-unmanned aerial vehicle coordination. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158497||Project:||C174||Abstract:||Advancements in robotics and control theory have equipped robots to communicate with one another and process data more quickly. Robot-to-robot communication enables multi-robot coordination. An abundance of benefits associated with multi-robot coordination includes increased overall performance, increased robustness, and completing complex tasks impossible for single robots. Current solutions often decompose the problem of multi-robot coordination into the problem of robot task allocation. These apply market-based distributed bidding models to allocate tasks. However, these market-based solutions do not necessarily provide guarantees of consistency, partition tolerance, and global ordering of operations. It is crucial to provide these guarantees to ensure that the individual views of the overall state of the robot swarm are the same across all robots. Failing to agree on a shared decision can cause significant ramifications, like system failures and threats to human life. Distributed consensus protocols, like Raft, provide these guarantees. Raft guarantees strong consistency with partition tolerance for system models with partial synchroneity, crash-recovery behaviour of nodes, and fair-loss links. This study aims to apply the Raft distributed consensus algorithm for multi-unmanned aerial vehicle (UAV) coordination in fire identification with applied interdisciplinary knowledge from computer science. This study shows that Raft maintains a consistent global view across different UAVs. Hence, this study illustrates the application of Raft distributed consensus algorithm through a simulation of 3 UAVs to explore a map and establish a shared global view of the states of the map. Also, this study measures the performance of the Raft distributed consensus algorithm for multi-unmanned aerial vehicle (UAV) coordination.||URI:||https://hdl.handle.net/10356/158497||Schools:||School of Mechanical and Aerospace Engineering||Organisations:||TUMCREATE||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Student Reports (FYP/IA/PA/PI)|
Updated on Dec 7, 2023
Updated on Dec 7, 2023
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