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The swift advancement of unmanned aerial vehicle (UAV) technologies necessitates new standards for developing human-drone interaction (HDI) interfaces.
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A. Menshchikov, D. Shadrin, V. Prutyanov, D. Lopatkin, S. Sosnin, E. Tsykunov, E. Iakovlev, and A. Somov, “Real-Time Detection of Hogweed: UAV Platform Empowered by Deep Learning,” IEEE Transactions on Computers , vol. 70, no. 8, pp. 1175–1188, 2021
2021
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I. Kalinov, D. Trinitatova, and D. Tsetserukou, “WareVR: Virtual Reality Interface for Supervision of Autonomous Robotic System Aimed at Warehouse Stocktaking,” in 2021 IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC) . IEEE, 2021, pp. 2139–2145
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2021
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2021
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P. Ponomareva, D. Trinitatova, A. Fedoseev, I. Kalinov, and D. Tsetserukou, “GraspLook: a VR-based Telemanipulation System with R-CNN-driven Augmentation of Virtual Environment,” in 2021 20th Int. Conf. on Advanced Robotics (ICAR) . IEEE, 2021, pp. 166–171
2021
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M. Wonsick, T. Keleștemur, S. Alt, and T. Padır, “Telemanipulation via Virtual Reality Interfaces with Enhanced Environment Models,” in 2021 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS) . IEEE, 2021, pp. 2999–3004
2021
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E. Nazarova, O. Sautenkov, M. A. Cabrera, J. Tirado, V. Serpiva, V. Rakhmatulin, and D. Tsetserukou, “CobotAR: Interaction with Robots using Omnidirectionally Projected Image and DNN-based Gesture Recognition,” in 2021 IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC) . IEEE, 2021, pp. 2590–2595
2021
Cited alongside, same era.
2023
Later among the works it cites.
X. Zhai, Z. Huang, T. Li, H. Liu, and S. Wang, “YOLO-Drone: An Optimized YOLOv8 Network for Tiny UAV Object Detection,” Electronics , vol. 12, no. 17, p. 3664, 2023
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D. Mourtzis, J. Angelopoulos, and N. Panopoulos, “Unmanned Aerial Vehicle (UAV) path planning and control assisted by Augmented Reality (AR): the case of indoor drones,” International Journal of Production Research , vol. 62, no. 9, pp. 3361–3382, 2024
2024
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