Abstract
In the UAV path planning study, due to the relative movement of multiple targets and the drone, long-term and large-scale UAV autonomous tracking has not been achieved. Therefore, aiming at this problem, this paper uses multiple moving target tracking algorithm to provide a real-time feedback on target position, estimates the later motion state of the target according to its position, and then performs the dynamic path planning by combining the feedback data and the state estimation result. Finally, The UAV path is optimized in real time. Experiments show that the proposed scheme can better plan the UAV path when multiple targets are in motion, thus improving the intelligence of the drone and the capability of long-time tracking.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Project No. 41701531. It was also supported in part by the Natural Science Foundation of Jiangsu Province under Project No. BK20170782. And this work was supported by the Open Research Fund of State Key Laboratory of Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing under grant No. 2016-ZW-KFJJ-01.
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Wang, B., Bao, J., Zhang, L. (2020). UAV Autonomous Path Optimization Simulation Based on Multiple Moving Target Tracking Prediction. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_164
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DOI: https://doi.org/10.1007/978-981-13-6504-1_164
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