The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Evolutionary route planner for unmanned air vehicles
Abstract
Based on evolutionary computation, a novel real-time route planner for unmanned air vehicles is presented. In the evolutionary route planner, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is not required. The planner incorporates domain-specific knowledge, can handle unforeseeable changes of the environment, and take into account different kinds of mission constraints such as minimum route leg length and flying altitude, maximum turning angle, and fixed approach vector to goal position. Furthermore, the novel planner can be used to plan routes both for a single vehicle and for multiple ones. With Digital Terrain Elevation Data, the resultant routes can increase the surviving probability of the vehicles using the terrain masking effect.
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Citations
Cites
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
Kavraki, L. E., Svestka, P., Latombe, J.-C., & Overmars, M. H. (1996) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.508439 · Cited by 6,343
Cited by
Fu, Y., Ding, M., & Zhou, C. (2012) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/tsmca.2011.2159586 · Cited by 256
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Metadata
- Authors
- Zheng, C., Li, L., Xu, F., Sun, F., & Ding, M.
- Venue
- IEEE Transactions on Robotics
- Published
- 2005-08
- Volume
- 21
- Issue
- 4
- Pages
- 609-620
- ISSN
- 1552-3098 (ISSN-L)
- OpenAlex
- W2154207837
- Cited by
- 266
- References
- 1
- FWCI
- 6.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zheng, C., Li, L., Xu, F., Sun, F., & Ding, M. (2005). Evolutionary route planner for unmanned air vehicles. IEEE Transactions on Robotics. https://doi.org/10.1109/tro.2005.844684
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