Marko Bertogna
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View article: Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation
Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation Open
Accurate mapping of agricultural field boundaries is essential for the efficient operation of agriculture. Automatic extraction from high-resolution satellite imagery, supported by computer vision techniques, can avoid costly ground survey…
View article: BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy
BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy Open
We present the BETTY dataset, a large-scale, multi-modal dataset collected on several autonomous racing vehicles, targeting supervised and self-supervised state estimation, dynamics modeling, motion forecasting, perception, and more. Exist…
View article: Enabling Containerisation of Distributed Applications with Real-Time Constraints
Enabling Containerisation of Distributed Applications with Real-Time Constraints Open
Containerisation is becoming a cornerstone of modern distributed systems, thanks to their lightweight virtualisation, high portability, and seamless integration with orchestration tools such as Kubernetes. The usage of containers has also …
View article: Human-Machine Interfaces in Safety-Related Cooperative Driving Automation Systems
Human-Machine Interfaces in Safety-Related Cooperative Driving Automation Systems Open
The main objective of connected vehicles is to significantly improve safety for travel participants and nearby people. Cooperative Driving Automation denotes the set of autonomous applications requiring cooperation among connected vehicles…
View article: Addressing challenges in industrial pick and place: A deep learning-based 6 Degrees-of-Freedom pose estimation solution
Addressing challenges in industrial pick and place: A deep learning-based 6 Degrees-of-Freedom pose estimation solution Open
Object picking is a fundamental, long-lasting, and yet unsolved problem in industrial applications. To complete it, 6 Degrees-of-Freedom pose estimation can be crucial. This task, easy for humans, is a challenge for machines as it involves…
View article: Guess the Drift with LOP-UKF: LiDAR Odometry and Pacejka Model for Real-Time Racecar Sideslip Estimation
Guess the Drift with LOP-UKF: LiDAR Odometry and Pacejka Model for Real-Time Racecar Sideslip Estimation Open
The sideslip angle, crucial for vehicle safety and stability, is determined using both longitudinal and lateral velocities. However, measuring the lateral component often necessitates costly sensors, leading to its common estimation, a top…
View article: er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds
er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds Open
The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at an unprecedented speed and in a head-to-head scenario, using independently developed software on open-wheel race c…
View article: A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data
A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data Open
Despite the availability of international prize-money competitions, scaled\nvehicles, and simulation environments, research on autonomous racing and the\ncontrol of sports cars operating close to the limit of handling has been\nlimited by …
View article: A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential
A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential Open
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. The model is used in a Model Predictive Controller in which we included a micro-steps …
View article: A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential
A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential Open
In this paper, we present a novel formulation to
\n model the effects of a locked differential on the lateral dynamics
\n of an autonomous open-wheel race car. The model is used in a
\nModel Predictive Controller in which we included a mic…
View article: er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds
er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds Open
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. T…
View article: Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques
Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques Open
The automated process of determining the crop type carried on plots of land, leveraging data provided by earth observation satellites, represents a highly valuable ability that can serve as a foundation for subsequent analyses or as input …
View article: Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation
Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation Open
In recent years, there has been a growing trend of using data-driven methods in industrial settings. These kinds of methods often process video images or parts, therefore the integrity of such images is crucial. Sometimes datasets, e.g. co…
View article: A benchmark analysis of data‐driven and geometric approaches for robot ego‐motion estimation
A benchmark analysis of data‐driven and geometric approaches for robot ego‐motion estimation Open
In the last decades, ego‐motion estimation or visual odometry (VO) has received a considerable amount of attention from the robotic research community, mainly due to its central importance in achieving robust localization and, as a consequ…
View article: Deep Image Prior for medical image denoising, a study about parameter initialization
Deep Image Prior for medical image denoising, a study about parameter initialization Open
Convolutional Neural Networks are widely known and used architectures in image processing contexts, in particular for medical images. These Deep Learning techniques, known for their ability to extract high-level features, almost always req…
View article: CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning
CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning Open
Perceiving the surrounding environment is essential for enabling autonomous or assisted driving functionalities. Common tasks in this domain include detecting road users, as well as determining lane boundaries and classifying driving condi…
View article: Mapping, Scheduling, and Schedulability Analysis
Mapping, Scheduling, and Schedulability Analysis Open
This chapter presents how the P-SOCRATES framework addresses the issue of scheduling multiple real-time tasks (RT tasks), made of multiple and concurrent non-preemptable task parts. In its most generic form, the scheduling problem in the a…
View article: Introduction
Introduction Open
This chapter provides an overview of the book theme, motivating the need for high-performance and time-predictable embedded computing. It describes the challenges introduced by the need for time-predictability on the one hand, and high-per…
View article: Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds
Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds Open
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 $m/s$. The used offline global trajectory…
View article: DCT-Former: Efficient Self-Attention with Discrete Cosine Transform
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform Open
Since their introduction the Trasformer architectures emerged as the dominating architectures for both natural language processing and, more recently, computer vision applications. An intrinsic limitation of this family of "fully-attentive…
View article: Deep learning-assisted analysis of automobiles handling performances
Deep learning-assisted analysis of automobiles handling performances Open
The luxury car market has demanding product development standards aimed at providing state-of-the-art features in the automotive domain. Handling performance is amongst the most important properties that must be assessed when developing a …
View article: The Predictable Execution Model in Practice
The Predictable Execution Model in Practice Open
Adoption of multi- and many-core processors in real-time systems has so far been slowed down, if not totally barred, due do the difficulty in providing analytical real-time guarantees on worst-case execution times. The Predictable Executio…
View article: All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers
All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers Open
Combining Natural Language with Vision represents a unique and interesting challenge in the domain of Artificial Intelligence. The AI City Challenge Track 5 for Natural Language-Based Vehicle Retrieval focuses on the problem of combining v…
View article: All You Can Embed: Natural Language based Vehicle Retrieval with\n Spatio-Temporal Transformers
All You Can Embed: Natural Language based Vehicle Retrieval with\n Spatio-Temporal Transformers Open
Combining Natural Language with Vision represents a unique and interesting\nchallenge in the domain of Artificial Intelligence. The AI City Challenge Track\n5 for Natural Language-Based Vehicle Retrieval focuses on the problem of\ncombinin…
View article: All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers
All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers Open
Combining Natural Language with Vision represents a unique and interesting challenge in the domain of Artificial Intelligence. The AI City Challenge Track 5 for Natural Language-Based Vehicle Retrieval focuses on the problem of combining v…
View article: SPHERE: A Multi-SoC Architecture for Next-Generation Cyber-Physical Systems Based on Heterogeneous Platforms
SPHERE: A Multi-SoC Architecture for Next-Generation Cyber-Physical Systems Based on Heterogeneous Platforms Open
This paper presents SPHERE, a project aimed at the realization of an integrated framework to abstract the hardware complexity of interconnected, modern system-on-chips (SoC) and simplify the management of their heterogeneous computational …