Affiliation:
1. Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
2. Department of Computer Systems Engineering, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
3. Information, Telecommunication and Control System Group, Nagaoka University of Technology, Niigata 940-2188, Japan
Abstract
UAVs have been contributing substantially to multi-disciplinary research and around 70% of the articles have been published in just about the last five years, with an exponential increase. Primarily, while exploring the literature from the scientific databases for various aspects within the autonomous UAV path planning, such as type and configuration of UAVs, the complexity of their environments or workspaces, choices of path generating algorithms, nature of solutions and efficacy of the generated paths, necessitates an increased number of search keywords as a prerequisite. However, the addition of more and more keywords might as well curtail some conducive and worthwhile search results in the same pursuit. This article presents a Systematic Literature Review (SLR) for 20 useful parameters, organized into six distinct categories that researchers and industry practitioners usually consider. In this work, Web of Science (WOS) was selected to search the primary studies based on three keywords: “Autonomous” + “Path Planning” + “UAV” and following the exclusion and inclusion criteria defined within the SLR methodology, 90 primary studies were considered. Through literature synthesis, a unique perspective to see through the literature is established in terms of characteristic research sectors for UAVs. Moreover, open research challenges from recent studies and state-of-the-art contributions to address them were highlighted. It was also discovered that the autonomy of UAVs and the extent of their mission complexities go hand-in-hand, and the benchmark to define a fully autonomous UAV is an arbitral goal yet to be achieved. To further this quest, the study cites two key models to measure a drone’s autonomy and offers a novel complexity matrix to measure the extent of a drone’s autonomy. Additionally, since preliminary-level researchers often look for technical means to assess their ideas, the technologies used in academic research are also tabulated with references.
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
Reference92 articles.
1. Systematic Literature Reviews in Engineering Education and Other Developing Interdisciplinary Fields;Borrego;J. Eng. Educ.,2014
2. PRISMA (2021, October 15). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Available online: https://www.prisma-statement.org/PRISMAStatement/.
3. Maw, A.A., Tyan, M., Nguyen, T.A., and Lee, J.W. (2021). iADA*-RL: Anytime Graph-Based Path Planning with Deep Reinforcement Learning for an Autonomous UAV. Appl. Sci., 11, (In English).
4. UAV autonomous path optimization simulation based on radar tracking prediction;Wang;EURASIP J. Wirel. Commun. Netw.,2018
5. Causa, F., Fasano, G., and Grassi, M. (2018). Multi-UAV Path Planning for Autonomous Missions in Mixed GNSS Coverage Scenarios. Sensors, 18, (In English).
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献