Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Costante, Gabriele"'
In the last decade, data-driven approaches have become popular choices for quadrotor control, thanks to their ability to facilitate the adaptation to unknown or uncertain flight conditions. Among the different data-driven paradigms, Deep Reinforcemen
Externí odkaz:
http://arxiv.org/abs/2410.07686
In multi-robot systems, relative localization between platforms plays a crucial role in many tasks, such as leader following, target tracking, or cooperative maneuvering. State of the Art (SotA) approaches either rely on infrastructure-based or on in
Externí odkaz:
http://arxiv.org/abs/2409.12780
Many of the existing works on quadrotor control address the trajectory tracking problem by employing a cascade design in which the translational and rotational dynamics are stabilized by two separate controllers. The stability of the cascade is often
Externí odkaz:
http://arxiv.org/abs/2409.05702
Autor:
Dionigi, Alberto, Leomanni, Mirko, Saviolo, Alessandro, Loianno, Giuseppe, Costante, Gabriele
Publikováno v:
2023 21st International Conference on Advanced Robotics (ICAR)
The capability to autonomously track a non-cooperative target is a key technological requirement for micro aerial vehicles. In this paper, we propose an output feedback control scheme based on deep reinforcement learning for controlling a micro aeria
Externí odkaz:
http://arxiv.org/abs/2312.17552
Publikováno v:
IEEE Robotics and Automation Letters 2024
Visual active tracking is a growing research topic in robotics due to its key role in applications such as human assistance, disaster recovery, and surveillance. In contrast to passive tracking, active tracking approaches combine vision and control c
Externí odkaz:
http://arxiv.org/abs/2308.16874
GaPT: Gaussian Process Toolkit for Online Regression with Application to Learning Quadrotor Dynamics
Autor:
Crocetti, Francesco, Mao, Jeffrey, Saviolo, Alessandro, Costante, Gabriele, Loianno, Giuseppe
Publikováno v:
2023 IEEE International Conference on Robotics and Automation (ICRA)
Gaussian Processes (GPs) are expressive models for capturing signal statistics and expressing prediction uncertainty. As a result, the robotics community has gathered interest in leveraging these methods for inference, planning, and control. Unfortun
Externí odkaz:
http://arxiv.org/abs/2303.08181
This paper presents the development of a system able to estimate the 2D relative position of nodes in a wireless network, based on distance measurements between the nodes. The system uses ultra wide band ranging technology and the Bluetooth Low Energ
Externí odkaz:
http://arxiv.org/abs/2212.06519
Autor:
Hernández-González, Israel Alejandro, García-Macías, Enrique, Costante, Gabriele, Ubertini, Filippo
Publikováno v:
In Mechanical Systems and Signal Processing 1 April 2024 211
Autor:
Cascianelli, Silvia, Costante, Gabriele, Devo, Alessandro, Ciarfuglia, Thomas A., Valigi, Paolo, Fravolini, Mario L.
Publikováno v:
IEEE Transactions on Multimedia, 22(1), 271-283 (2019)
Natural Language Video Description (NLVD) has recently received strong interest in the Computer Vision, Natural Language Processing (NLP), Multimedia, and Autonomous Robotics communities. The State-of-the-Art (SotA) approaches obtained remarkable res
Externí odkaz:
http://arxiv.org/abs/2102.05067
In the last decades, visual target tracking has been one of the primary research interests of the Robotics research community. The recent advances in Deep Learning technologies have made the exploitation of visual tracking approaches effective and po
Externí odkaz:
http://arxiv.org/abs/2009.13475