Search Results for author: Marko Bertogna

Found 9 papers, 5 papers with code

A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential

no code implementations22 Dec 2023 Ayoub Raji, Nicola Musiu, Alessandro Toschi, Francesco Prignoli, Eugenio Mascaro, Pietro Musso, Francesco Amerotti, Alexander Liniger, Silvio Sorrentino, Marko Bertogna

In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar.

er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

no code implementations27 Oct 2023 Ayoub Raji, Danilo Caporale, Francesco Gatti, Andrea Giove, Micaela Verucchi, Davide Malatesta, Nicola Musiu, Alessandro Toschi, Silviu Roberto Popitanu, Fabio Bagni, Massimiliano Bosi, Alexander Liniger, Marko Bertogna, Daniele Morra, Francesco Amerotti, Luca Bartoli, Federico Martello, Riccardo Porta

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using independently developed software on open-wheel racecars.

Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation

1 code implementation17 Apr 2023 Elena Govi, Davide Sapienza, Carmelo Scribano, Tobia Poppi, Giorgia Franchini, Paola Ardòn, Micaela Verucchi, Marko Bertogna

We analyze how the presence of the markers affects the pose estimation accuracy, and how this bias may be mitigated through data augmentation and other methods.

6D Pose Estimation Data Augmentation

Model-Based Underwater 6D Pose Estimation from RGB

no code implementations14 Feb 2023 Davide Sapienza, Elena Govi, Sara Aldhaheri, Marko Bertogna, Eloy Roura, Èric Pairet, Micaela Verucchi, Paola Ardón

All objects and scenes are made available in an open-source dataset that includes annotations for object detection and pose estimation.

6D Pose Estimation 6D Pose Estimation using RGB +4

Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds

no code implementations22 Jul 2022 Ayoub Raji, Alexander Liniger, Andrea Giove, Alessandro Toschi, Nicola Musiu, Daniele Morra, Micaela Verucchi, Danilo Caporale, Marko Bertogna

This paper presents a multi-layer motion planning and control architecture for autonomous racing, capable of avoiding static obstacles, performing active overtakes, and reaching velocities above 75 $m/s$.

Motion Planning

DCT-Former: Efficient Self-Attention with Discrete Cosine Transform

1 code implementation2 Mar 2022 Carmelo Scribano, Giorgia Franchini, Marco Prato, Marko Bertogna

Since their introduction the Trasformer architectures emerged as the dominating architectures for both natural language processing and, more recently, computer vision applications.

Data Compression

All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers

1 code implementation18 Jun 2021 Carmelo Scribano, Davide Sapienza, Giorgia Franchini, Micaela Verucchi, Marko Bertogna

Combining Natural Language with Vision represents a unique and interesting challenge in the domain of Artificial Intelligence.

Retrieval

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