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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Byeong-Min Jeong Jung-Su Ha Han-Lim Choi |
| Copyright Year | 2014 |
| Description | Author affiliation: Korea Aerosp. Ind., Sacheon, South Korea (Byeong-Min Jeong) || Div. of Aerosp. Eng., KAIST, Daejeon, South Korea (Jung-Su Ha; Han-Lim Choi) |
| Abstract | This paper presents a methodology to generate task flow for conducting a surveillance mission using multiple UAVs, when the goal is to persistently maintain the uncertainty level of surveillance regions as low as possible. The mission planning problem is formulated as a Markov decision process (MDP), which is a infinite-horizon discrete stochastic optimal control formulation and often leads to a periodic task flows to be implemented in a persistent manner. The method specifically focuses on reducing the size of decision space without losing key feature of the problem in order to mitigate the curse of dimensionality of MDP; integrating a task allocator to identify admissible actions is demonstrate to effectively reduce the decision space. Numerical simulations verify the applicability of the proposed decision scheme. |
| Starting Page | 831 |
| Ending Page | 834 |
| File Size | 699571 |
| Page Count | 4 |
| File Format | |
| ISSN | 20937121 |
| e-ISBN | 9788993215076 |
| DOI | 10.1109/ICCAS.2014.6987894 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-10-22 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Control, Robotics and Systems (ICROS) |
| Subject Keyword | Surveillance Autonomous Multi-UAV Systems Mission planning |
| Content Type | Text |
| Resource Type | Article |
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