Int. J. Simul. Multidisci. Des. Optim.
Volume 12, 2021
Advances in Modeling and Optimization of Manufacturing Processes
|Number of page(s)||8|
|Published online||27 October 2021|
- H. Shakhatreh, A.H. Sawalmeh, A. Al-Fuqaha, Z. Dou, E. Almaita, I. Khalil, M. Guizani, Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges, IEEE Access 7, 48572–48634 (2019) [Google Scholar]
- P. Radoglou-Grammatikis, P. Sarigiannidis, T. Lagkas, I. Moscholios, A compilation of UAV applications for precision agriculture, Comput. Netw. 172, 107148 (2020) [Google Scholar]
- S. Park, Y. Choi, Applications of unmanned aerial vehicles in mining from exploration to reclamation: A review, Minerals 10, 663 (2020) [CrossRef] [Google Scholar]
- A. Valsan, B. Parvathy, G.H. Vismaya Dev, R.S. Unnikrishnan, P.K. Reddy, A. Vivek, Unmanned aerial vehicle for search and rescue mission, in: 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184) (IEEE, 2020), pp. 684–687 [CrossRef] [Google Scholar]
- A. Sigala, B. Langhals, Applications of Unmanned Aerial Systems (UAS): A delphi study projecting future UAS missions and relevant challenges, Drones 4, 8 (2020) [CrossRef] [Google Scholar]
- B. Esakki, S. Mathiyazhagan, M. Moses, K.J. Rao, S. Ganesan, Development of 3D-printed floating Quadrotor for collection of algae in remote water bodies, Comput. Electron. Agric. 164, 104891 (2019) [CrossRef] [Google Scholar]
- H. Shin, J. Chae, A performance review of collision-free path planning algorithms, Electronics 9, 316 (2020) [CrossRef] [Google Scholar]
- S.K. Debnath, R. Omar, S. Bagchi, E.N. Sabudin, M.H.A.S. Kandar, K. Foysol, T.K. Chakraborty, Different cell decomposition path planning methods for unmanned air vehicles-A review, in: Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019, Springer, Singapore, 2020, pp. 99–111 [Google Scholar]
- D. González, J. Pérez, V. Milanés, F. Nashashibi, A review of motion planning techniques for automated vehicles, IEEE Trans. Intell. Transp. Syst. 17, 1135–1145 (2015) [Google Scholar]
- D.D. Zhu, J.Q. Sun, A new algorithm based on Dijkstra for vehicle path planning considering intersection attribute, IEEE Access 9, 19761–19775 (2021) [CrossRef] [Google Scholar]
- S. Wu, Y. Du, Y. Zhang, Mobile robot path planning based on a generalized wavefront algorithm, Math. Prob. Eng. 2020 (2020) [MathSciNet] [Google Scholar]
- D.R. Thompson, S. Chien, Y. Chao, P. Li, B. Cahill, J. Levin, O. Schofield et al., Spatiotemporal path planning in strong, dynamic, uncertain currents, in: 2010 IEEE International Conference on Robotics and Automation (IEEE, 2010), pp. 4778–4783 [CrossRef] [Google Scholar]
- S.H. Tang, C.F. Yeong, E.L.M. Su, Comparison between normal waveform and modified wavefront path planning algorithm for mobile robot, in: Applied Mechanics and Materials, vol. 607, Trans Tech Publications Ltd, 2014, pp. 778–781 [CrossRef] [Google Scholar]
- S. Koenig, M. Likhachev, D. Furcy, Lifelong Planning A*, Artif. Intell. 155, 93–146 (2004) [CrossRef] [Google Scholar]
- I. Noreen, A. Khan, Z. Habib, Optimal path planning using memory efficient A*, in: Proceedings of the IEEE International Conference on Frontiers of Information Technology, Islamabad, Pakistan, 19–21 December 2016, pp. 142–146 [Google Scholar]
- Z. Bu, R.E. Korf, A*+ BFHS: A hybrid heuristic search algorithm, arXiv preprint arXiv:2103.12701 (2021) [Google Scholar]
- K. Daniel, A. Nash, S. Koenig, Theta any-angle path planning on grids, J. Artif. Intell. Res. 39, 533–579 (2010) [CrossRef] [Google Scholar]
- C. Wu, X. Huang, Y. Luo, S. Leng, F. Wu, An improved sparse hierarchical lazy theta* algorithm for UAV real-time path planning in unknown three-dimensional environment, in: 2020 IEEE 20th International Conference on Communication Technology (ICCT), IEEE, 2020, pp. 673–677 [CrossRef] [Google Scholar]
- D. Ferguson, N. Kalra, A. Stentz, Replanning with RRTs, in: Proceedings of the IEEE International Conference on Robotics and Automation, Orlando, FL, USA, 15–19 May 2006 [Google Scholar]
- C.W. Warren, Fast path planning using modified A* method, in: Proceedings of the IEEE International Conference on Robotics and Automation, Atlanta, GA, USA, 2–6 May 1993 [Google Scholar]
- A. Botea, M. Muller, J. Schaeffer, Near optimal hierarchical path-finding, J. Game Dev. 1, 1–30 (2004) [Google Scholar]
- M. Radmanesh, M. Kumar, P.H. Guentert, M. Sarim, Overview of path-planning and obstacle avoidance algorithms for UAVs: A comparative study, Unmanned Syst. 6, 95–118 (2018) [CrossRef] [Google Scholar]
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