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pro vyhledávání: '"P Pretto"'
Robotic fruit monitoring is a key step toward automated agricultural production systems. Robots can significantly enhance plant and temporal fruit monitoring by providing precise, high-throughput assessments that overcome the limitations of tradition
Externí odkaz:
http://arxiv.org/abs/2411.07799
The advent of generalist Large Language Models (LLMs) and Large Vision Models (VLMs) have streamlined the construction of semantically enriched maps that can enable robots to ground high-level reasoning and planning into their representations. One of
Externí odkaz:
http://arxiv.org/abs/2411.02938
Semantic segmentation of point clouds is an essential task for understanding the environment in autonomous driving and robotics. Recent range-based works achieve real-time efficiency, while point- and voxel-based methods produce better results but ar
Externí odkaz:
http://arxiv.org/abs/2410.10510
When numerically solving Einstein's equations for the evolution of binary black holes, physical imperfections in the initial data manifest as a transient, high-frequency pulse of ''junk radiation.'' This unphysical signal must be removed before the w
Externí odkaz:
http://arxiv.org/abs/2407.20470
Autor:
Olivastri, Emilio, Pretto, Alberto
Publikováno v:
2024 IEEE International Conference on Robotics and Automation (ICRA), 2024, pp. 10283-10289
In SLAM (Simultaneous localization and mapping) problems, Pose Graph Optimization (PGO) is a technique to refine an initial estimate of a set of poses (positions and orientations) from a set of pairwise relative measurements. The optimization procedu
Externí odkaz:
http://arxiv.org/abs/2405.08503
Publikováno v:
IEEE ICRA Workshop on Field Robotics 2024
The increasing demand for underwater vehicles highlights the necessity for robust localization solutions in inspection missions. In this work, we present a novel real-time sonar-based underwater global positioning algorithm for AUVs (Autonomous Under
Externí odkaz:
http://arxiv.org/abs/2405.01971
Publikováno v:
Proceedings of the 2024 International Conference on 3D Vision (3DV)
Neural Radiance Fields (NeRFs) have shown impressive results for novel view synthesis when a sufficiently large amount of views are available. When dealing with few-shot settings, i.e. with a small set of input views, the training could overfit those
Externí odkaz:
http://arxiv.org/abs/2403.14412
The Mini-EUSO telescope is the first space-based detector of the JEM-EUSO program. It was launched for the International Space Station on August 22$^{nd}$, 2019 to observe from the ISS orbit ($\sim$420 km altitude) various phenomena occurring in the
Externí odkaz:
http://arxiv.org/abs/2309.11920
Autor:
Donadi, Ivano, Olivastri, Emilio, Fusaro, Daniel, Li, Wanmeng, Evangelista, Daniele, Pretto, Alberto
Publikováno v:
Proceedings of the 14th International Conference on Computer Vision Systems (ICVS 2023)
Autonomous navigation in underwater environments presents challenges due to factors such as light absorption and water turbidity, limiting the effectiveness of optical sensors. Sonar systems are commonly used for perception in underwater operations a
Externí odkaz:
http://arxiv.org/abs/2308.01058
Autor:
Donadi, Ivano, Pretto, Alberto
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 4, pp. 3498-3505, April 2024
Object pose estimation is a fundamental computer vision task exploited in several robotics and augmented reality applications. Many established approaches rely on predicting 2D-3D keypoint correspondences using RANSAC (Random sample consensus) and es
Externí odkaz:
http://arxiv.org/abs/2307.11543