Multi-agent informed path planning using the probability hypothesis density
Author:
Funder
Horizon 2020
Norges Forskningsråd
Centrum för Industriell Informationsteknologi, Linköpings Universitet
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
http://link.springer.com/content/pdf/10.1007/s10514-020-09904-1.pdf
Reference38 articles.
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2. Chekuri, C., & Pál, M. (2005). A recursive greedy algorithm for walks in directed graphs. In Proceedings—Annual IEEE Symposium on Foundations of Computer Science, FOCS, Pittsburgh, PA, USA (pp. 245–253). https://doi.org/10.1109/SFCS.2005.9.
3. Chen, S. G. (2014). Reduced recursive inclusion-exclusion principle for the probability of union events. In IEEE International Conference on Industrial Engineering and Engineering Management, Bandar Sunway, Malaysia (pp. 5–7). https://doi.org/10.1109/IEEM.2014.7058590.
4. Dames, P. (2017). Distributed multi-target search and tracking using the PHD filter. In. 2017 International Symposium on Multi-Robot and Multi-Agent Systems (MRS). IEEE. https://doi.org/10.1109/mrs.2017.8250924.
5. Dames, P. (2019). Distributed multi-target search and tracking using the PHD filter. Autonomous Robots. https://doi.org/10.1007/s10514-019-09840-9.
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