Abstract
This work presents an unmanned aerial vehicle (UAV) planning algorithm for local defense of a system from enemy UAVs that come to attack or reconnoiter the system. Planning with non-cooperative moving targets often leads to difficulties in utilizing the widely-used path planning algorithms, since their intention and path plans are not known. Furthermore, because a destination of our UAVs path plan can be changed over time, a fast path planning algorithm which can deal with various obstacles is needed. To handle these problems, two key methods are adopted in this work: First, an informative planning is used for predicting each path of enemy UAVs. Second, the iterative linear quadratic regulator algorithm (iLQR) is utilized to derive feasible paths in a mission environment. Utilizing the two methods, the system predicts paths of invading UAVs and allocates friend UAVs to dominate enemies. Finally, each path for an allocated task is computed via iLQR.
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Acknowledgements
This research was sponsored by the Agency for Defense Development under the grant UD170016RD.
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Chae, HJ., Park, SS., Kim, HV., Ko, HS., Choi, HL. (2020). UAV Path Planning for Local Defense Systems. In: P. P. Abdul Majeed, A., Mat-Jizat, J., Hassan, M., Taha, Z., Choi, H., Kim, J. (eds) RITA 2018. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-8323-6_17
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DOI: https://doi.org/10.1007/978-981-13-8323-6_17
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