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Alberto Dionigi
Titolo
Citata da
Citata da
Anno
Enhancing continuous control of mobile robots for end-to-end visual active tracking
A Devo, A Dionigi, G Costante
Robotics and Autonomous Systems 142, 103799, 2021
192021
E-vat: An asymmetric end-to-end approach to visual active exploration and tracking
A Dionigi, A Devo, L Guiducci, G Costante
IEEE Robotics and Automation Letters 7 (2), 4259-4266, 2022
152022
ARD‐VO: Agricultural robot data set of vineyards and olive groves
F Crocetti, E Bellocchio, A Dionigi, S Felicioni, G Costante, ML Fravolini, ...
Journal of Field Robotics 40 (6), 1678-1696, 2023
62023
Integrating Sparse Learning-Based Feature Detectors into Simultaneous Localization and Mapping—A Benchmark Study
G Mollica, M Legittimo, A Dionigi, G Costante, P Valigi
Sensors 23 (4), 2286, 2023
52023
A benchmark analysis of data‐driven and geometric approaches for robot ego‐motion estimation
M Legittimo, S Felicioni, F Bagni, A Tagliavini, A Dionigi, F Gatti, ...
Journal of Field Robotics 40 (3), 626-654, 2023
22023
D-VAT: End-to-End Visual Active Tracking for Micro Aerial Vehicles
A Dionigi, S Felicioni, M Leomanni, G Costante
IEEE Robotics and Automation Letters, 2024
12024
Exploring deep reinforcement learning for robust target tracking using micro aerial vehicles
A Dionigi, M Leomanni, A Saviolo, G Loianno, G Costante
2023 21st International Conference on Advanced Robotics (ICAR), 506-513, 2023
12023
A convex programming approach to multipoint optimal motion planning for unicycle robots
M Leomanni, G Mollica, A Dionigi, P Valigi, G Costante
IEEE Control Systems Letters 7, 1688-1693, 2023
12023
Quadrotor Control System Design for Robust Monocular Visual Tracking
M Leomanni, F Ferrante, A Dionigi, G Costante, P Valigi, ML Fravolini
IEEE Transactions on Control Systems Technology, 2024
2024
W. Wang, Z. Wu, C. Saija, A. Zeidan, Z. Xu, A. Pishkahi, T. Patterson, S. Redwood, S. Wang, K. Rhode, and R. Housden 5254
A Dionigi, S Felicioni, M Leomanni, G Costante, H Chen, W Xu, W Guo, ...
Visual Active Exploration and Tracking: a Deep Reinforcement Learning Approach
A Dionigi, A Devo, L Guiducci, P Valigi, G Costante
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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