References
Kuriki Y, Namerikawa T. Consensus-based cooperative formation control with collision avoidance for a multi-UAV system. In: Proceedings of 2014 American Control Conference (ACC), 2014. 2077–2082
Sunberg Z N, Kochenderfer M J, Pavone M. Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming. In: Processding of 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, 2016. 1455–1461
Carbone C, Ciniglio U, Corraro F, et al. A novel 3D geometric algorithm for aircraft autonomous collision avoidance. In: Proceedings of the 45th IEEE Conference on Decision and Control, San Diego, 2006. 1580–1585
Lai J, Mejias L, Ford J J. Airborne vision-based collision-detection system. J Field Robot, 2011, 28: 137–157
Accardo D, Fasano G, Forlenza L, et al. Flight test of a radar-based tracking system for UAS sense and avoid. IEEE Trans Aerosp Electron Syst, 2013, 49: 1139–1160
Andersson O, Wzorek M, Rudol P, et al. Modelpredictive control with stochastic collision avoidance using Bayesian policy optimization. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2016. 4597–4604
Hennes D, Meeussen W, Tuyls K. Multi-robot collision avoidance with localization uncertainty. In: Proceedings of International Conference on Autonomous Agents and Multiagent Systems, Singapore, 2016. 147–154
Alejo D, Conde R, Cobano J A, et al. Multi-UAV collision avoidance with separation assurance under uncertainties. In: Proceedings of IEEE International Conference on Mechatronics, 2009. 1–6
Wang S C, Lyu Y, Ren W. Unscented-transformationbased distributed nonlinear state estimation: algorithm, analysis, and experiments. IEEE Trans Contr Syst Technol, 2018. doi: 10.1109/TCST.2018.2847290
Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 61603303, 61473230), Natural Science Foundation of Shaanxi Province (Grant Nos. 2017JQ6005, 2017JM6027), China Postdoctoral Science Foundation (Grant No. 2017M610650), and Fundamental Research Funds for the Central Universities (Grant No. 3102017JQ02011).
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Supplementary material, approximately 30.8 MB.
Rights and permissions
About this article
Cite this article
Lyu, Y., Pan, Q., Hu, J. et al. Obstacle avoidance under relative localization uncertainty. Sci. China Inf. Sci. 62, 84201 (2019). https://doi.org/10.1007/s11432-018-9760-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11432-018-9760-9