Rapid location technology of odor sources by multi‐UAV
Author:
Affiliation:
1. International Union for Conservation of Nature (IUCN), School of Automation Nanjing University of Information Science and Technology Nanjing China
Publisher
Wiley
Subject
Computer Science Applications,Control and Systems Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/rob.22066
Reference40 articles.
1. Bao P.X. Cheng L. Wu Q.X. Yao D. Yu Q.Y.&Wang X.(2019) Multi‐UAV gas concentration map fusion using the image repair algorithm based on clustered directed diffusion model. In:2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN). IEEE pp.1–4. Available from:https://doi.org/10.1109/ISOEN.2019.8823369
2. Environmental chemical sensing using small drones: A review
3. Odor source localization algorithms on mobile robots: A review and future outlook
4. Che H. Shi C. Xu X. Li J.&Wu B.(2018) Research on improved aco algorithm‐based multi‐robot odor source localization. In:2018 2nd International Conference on Robotics and Automation Sciences (ICRAS). IEEE pp.1–5. Available from:https://doi.org/10.1109/ICRAS.2018.8443237
5. Combining particle filter algorithm with bio-inspired anemotaxis behavior: A smoke plume tracking method and its robotic experiment validation
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