Abstract
The autonomous route planning in coverage search is an important subject of unmanned aerial vehicle (UAV) mission planning. Pre-planning is simple and feasible for the coverage search mission of single UAV in regular areas. As to the dynamic mission in complicated environment of multi-UAV, the route planning will encounter the difficulties of reasonable task distribution and the real-time environment changes which include the changes of the mission area, the detection of threat area, the interference of communication and so on. At this point, making the UAV to do real-time autonomous planning is necessary. However, it is hard to fulfil requirements of real-time, autonomous and efficient at the same time. According to a scalable knowledge base, this paper proposes a coverage search algorithm which is based on the mapping between the basic behavior combination and surroundings. A UAV’s coverage search simulation model with random shapes is built with a discrete map to update the environment and the changes of the mission on time. Comparison of the simulation analysis and the dynamic programming shows that the method has amazing expandability and can change the search strategy feasibly. It is efficient, and the ratio of coverage redundancy can be decreased to 1.21. It also has the potentiality in real-time calculation, and the computing time can be shortened to about 2 s.
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Foundation item: the Postdoctoral Science Foundation of China (No. 2015M582881)
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Chen, Z., Lu, Y., Hou, Z. et al. UAV’s Coverage Search Planning Algorithm Based on Action Combinations. J. Shanghai Jiaotong Univ. (Sci.) 24, 48–57 (2019). https://doi.org/10.1007/s12204-018-2010-1
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DOI: https://doi.org/10.1007/s12204-018-2010-1