Zobrazeno 1 - 10
of 1 093
pro vyhledávání: '"GIAMMARINO A"'
Autor:
Di Giammarino, Luca, Sun, Boyang, Grisetti, Giorgio, Pollefeys, Marc, Blum, Hermann, Barath, Daniel
Accurate localization in diverse environments is a fundamental challenge in computer vision and robotics. The task involves determining a sensor's precise position and orientation, typically a camera, within a given space. Traditional localization me
Externí odkaz:
http://arxiv.org/abs/2407.15593
We propose C-LAIfO, a computationally efficient algorithm designed for imitation learning from videos in the presence of visual mismatch between agent and expert domains. We analyze the problem of imitation from expert videos with visual discrepancie
Externí odkaz:
http://arxiv.org/abs/2407.12792
Adversarial Imitation Learning (AIL) faces challenges with sample inefficiency because of its reliance on sufficient on-policy data to evaluate the performance of the current policy during reward function updates. In this work, we study the convergen
Externí odkaz:
http://arxiv.org/abs/2405.16668
LiDAR odometry is the task of estimating the ego-motion of the sensor from sequential laser scans. This problem has been addressed by the community for more than two decades, and many effective solutions are available nowadays. Most of these systems
Externí odkaz:
http://arxiv.org/abs/2405.05828
Autor:
Brizi, Leonardo, Giacomini, Emanuele, Di Giammarino, Luca, Ferrari, Simone, Salem, Omar, De Rebotti, Lorenzo, Grisetti, Giorgio
This paper presents a vision and perception research dataset collected in Rome, featuring RGB data, 3D point clouds, IMU, and GPS data. We introduce a new benchmark targeting visual odometry and SLAM, to advance the research in autonomous robotics an
Externí odkaz:
http://arxiv.org/abs/2404.11322
Autor:
Sabouni, Ehsan, Ahmad, H. M. Sabbir, Giammarino, Vittorio, Cassandras, Christos G., Paschalidis, Ioannis Ch., Li, Wenchao
Optimal control methods provide solutions to safety-critical problems but easily become intractable. Control Barrier Functions (CBFs) have emerged as a popular technique that facilitates their solution by provably guaranteeing safety, through their f
Externí odkaz:
http://arxiv.org/abs/2403.17338
Autor:
Bronsch, Wibke, Tuniz, Manuel, Puntel, Denny, Giammarino, Alessandro, Parmigiani, Fulvio, Chan, Yang-hao, Cilento, Federico
Complex materials encompassing different phases of matter can display new photoinduced metastable states differing from those attainable under equilibrium conditions. These states can be realized when energy is injected in the material following a no
Externí odkaz:
http://arxiv.org/abs/2403.03805
This paper investigates how to incorporate expert observations (without explicit information on expert actions) into a deep reinforcement learning setting to improve sample efficiency. First, we formulate an augmented policy loss combining a maximum
Externí odkaz:
http://arxiv.org/abs/2402.18836
In this work, we focus on a robotic unloading problem from visual observations, where robots are required to autonomously unload stacks of parcels using RGB-D images as their primary input source. While supervised and imitation learning have accompli
Externí odkaz:
http://arxiv.org/abs/2309.06621
Autor:
Benedetta Torsiello, Mauro Giammarino, Piero Quatto, Monica Battini, Silvana Mattiello, Luca Battaglini, Manuela Renna
Publikováno v:
Italian Journal of Animal Science, Vol 23, Iss 1, Pp 938-960 (2024)
This study focuses on assessing inter-observer reliability (IOR) between two observers in the case of trichotomous and four-level animal-based welfare indicators assessed at individual level. The Body Condition Score (BCS) and Knee calluses (KNC) wer
Externí odkaz:
https://doaj.org/article/cbecb9bd9ad04ce9a2054610e038da9f
