Autonomous Strike UAVs for Counterterrorism Missions: Challenges and Preliminary Solutions

Autor:	Aljohani, Meshari, Mukkamalai, Ravi, Olariu, Stephen
Rok vydání:	2024
Předmět:	Computer Science - Robotics Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Unmanned Aircraft Vehicles (UAVs) are becoming a crucial tool in modern warfare, primarily due to their cost-effectiveness, risk reduction, and ability to perform a wider range of activities. The use of autonomous UAVs to conduct strike missions against highly valuable targets is the focus of this research. Due to developments in ledger technology, smart contracts, and machine learning, such activities formerly carried out by professionals or remotely flown UAVs are now feasible. Our study provides the first in-depth analysis of challenges and preliminary solutions for successful implementation of an autonomous UAV mission. Specifically, we identify challenges that have to be overcome and propose possible technical solutions for the challenges identified. We also derive analytical expressions for the success probability of an autonomous UAV mission, and describe a machine learning model to train the UAV. Comment: 12 pages, 12 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.01022 Zobrazit plný text záznamu View this record from Arxiv