Search Results for author: Giuseppe Loianno

Found 21 papers, 7 papers with code

Learning to Fly in Seconds

2 code implementations22 Nov 2023 Jonas Eschmann, Dario Albani, Giuseppe Loianno

Our framework enables Simulation-to-Reality (Sim2Real) transfer for direct RPM control after only 18 seconds of training on a consumer-grade laptop as well as its deployment on microcontrollers to control a multirotor under real-time guarantees.

Reinforcement Learning (RL)

Visual Environment Assessment for Safe Autonomous Quadrotor Landing

no code implementations16 Nov 2023 Mattia Secchiero, Nishanth Bobbili, Yang Zhou, Giuseppe Loianno

Autonomous identification and evaluation of safe landing zones are of paramount importance for ensuring the safety and effectiveness of aerial robots in the event of system failures, low battery, or the successful completion of specific tasks.

Visual Geo-localization with Self-supervised Representation Learning

no code implementations31 Jul 2023 Jiuhong Xiao, Gao Zhu, Giuseppe Loianno

In this work, we present a novel unified VG-SSL framework with the goal to enhance performance and training efficiency on a large VG dataset by SSL methods.

Representation Learning Self-Supervised Learning

RLtools: A Fast, Portable Deep Reinforcement Learning Library for Continuous Control

1 code implementation6 Jun 2023 Jonas Eschmann, Dario Albani, Giuseppe Loianno

Finally, RLtools enables the first-ever demonstration of training a deep RL algorithm directly on a microcontroller, giving rise to the field of Tiny Reinforcement Learning (TinyRL).

Continuous Control reinforcement-learning +1

Long-range UAV Thermal Geo-localization with Satellite Imagery

1 code implementation5 Jun 2023 Jiuhong Xiao, Daniel Tortei, Eloy Roura, Giuseppe Loianno

This paper proposes a novel thermal geo-localization framework using satellite RGB imagery, which includes multiple domain adaptation methods to address the limited availability of paired thermal and satellite images.

Domain Adaptation Visual Place Recognition

PENet: A Joint Panoptic Edge Detection Network

1 code implementation15 Mar 2023 Yang Zhou, Giuseppe Loianno

In recent years, compact and efficient scene understanding representations have gained popularity in increasing situational awareness and autonomy of robotic systems.

Edge Detection Multi-Task Learning +2

Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control

no code implementations23 Oct 2022 Alessandro Saviolo, Jonathan Frey, Abhishek Rathod, Moritz Diehl, Giuseppe Loianno

Model-based control requires an accurate model of the system dynamics for precisely and safely controlling the robot in complex and dynamic environments.

Active Learning Model Predictive Control +1

Vision-based Perimeter Defense via Multiview Pose Estimation

no code implementations25 Sep 2022 Elijah S. Lee, Giuseppe Loianno, Dinesh Jayaraman, Vijay Kumar

Previous studies in the perimeter defense game have largely focused on the fully observable setting where the true player states are known to all players.

Pose Estimation

Coexistence of UAVs and Terrestrial Users in Millimeter-Wave Urban Networks

no code implementations19 Sep 2022 Seongjoon Kang, Marco Mezzavilla, Angel Lozano, Giovanni Geraci, Sundeep Rangan, Vasilii Semkin, William Xia, Giuseppe Loianno

5G millimeter-wave (mmWave) cellular networks are in the early phase of commercial deployments and present a unique opportunity for robust, high-data-rate communication to unmanned aerial vehicles (UAVs).

Physics-Inspired Temporal Learning of Quadrotor Dynamics for Accurate Model Predictive Trajectory Tracking

1 code implementation7 Jun 2022 Alessandro Saviolo, Guanrui Li, Giuseppe Loianno

In this paper, we present a novel Physics-Inspired Temporal Convolutional Network (PI-TCN) approach to learning quadrotor's system dynamics purely from robot experience.

Model Predictive Control

Multi-Robot Collaborative Perception with Graph Neural Networks

no code implementations5 Jan 2022 Yang Zhou, Jiuhong Xiao, Yue Zhou, Giuseppe Loianno

Multi-robot systems such as swarms of aerial robots are naturally suited to offer additional flexibility, resilience, and robustness in several tasks compared to a single robot by enabling cooperation among the agents.

Decision Making Monocular Depth Estimation +1

VIPose: Real-time Visual-Inertial 6D Object Pose Tracking

no code implementations27 Jul 2021 Rundong Ge, Giuseppe Loianno

Estimating the 6D pose of objects is beneficial for robotics tasks such as transportation, autonomous navigation, manipulation as well as in scenarios beyond robotics like virtual and augmented reality.

Autonomous Navigation Object +2

Millimeter-Wave UAV Coverage in Urban Environments

1 code implementation5 Apr 2021 Seongjoon Kang, Marco Mezzavilla, Angel Lozano, Giovanni Geraci, William Xia, Sundeep Rangan, Vasilii Semkin, Giuseppe Loianno

Additional dedicated (rooftop-mounted and uptilted) base stations strengthen the coverage provided that their density is comparable to that of the standard deployment, and would be instrumental for sparse deployments of the latter.

Lightweight UAV-based Measurement System for Air-to-Ground Channels at 28 GHz

no code implementations31 Mar 2021 Vasilii Semkin, Seongjoon Kang, Jaakko Haarla, William Xia, Ismo Huhtinen, Giovanni Geraci, Angel Lozano, Giuseppe Loianno, Marco Mezzavilla, Sundeep Rangan

Wireless communication at millimeter wave frequencies has attracted considerable attention for the delivery of high-bit-rate connectivity to unmanned aerial vehicles (UAVs).

Comparative Analysis of Agent-Oriented Task Assignment and Path Planning Algorithms Applied to Drone Swarms

no code implementations13 Jan 2021 Rohith Gandhi Ganesan, Samantha Kappagoda, Giuseppe Loianno, David K. A. Mordecai

In this work, we choose the task of optimal coverage of an environment with drone swarms where the global knowledge of the goal states and its positions are known but not of the obstacles.

Robotics Systems and Control Systems and Control

Generative Neural Network Channel Modeling for Millimeter-Wave UAV Communication

no code implementations16 Dec 2020 William Xia, Sundeep Rangan, Marco Mezzavillla, Angel Lozano, Giovanni Geraci, Vasilii Semkin, Giuseppe Loianno

The millimeter wave bands are being increasingly considered for wireless communication to unmanned aerial vehicles (UAVs).

Millimeter Wave Channel Modeling via Generative Neural Networks

no code implementations25 Aug 2020 William Xia, Sundeep Rangan, Marco Mezzavilla, Angel Lozano, Giovanni Geraci, Vasilii Semkin, Giuseppe Loianno

Statistical channel models are instrumental to design and evaluate wireless communication systems.

Millimeter Wave Remove UAV Control and Communications for Public Safety Scenarios

no code implementations13 May 2020 William Xia, Michele Polese, Marco Mezzavilla, Giuseppe Loianno, Sundeep Rangan, Michele Zorzi

Communication and video capture from unmanned aerial vehicles (UAVs) offer significant potential for assisting first responders in remote public safety settings.

U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification

no code implementations18 Sep 2018 Ty Nguyen, Tolga Ozaslan, Ian D. Miller, James Keller, Giuseppe Loianno, Camillo J. Taylor, Daniel D. Lee, Vijay Kumar, Joseph H. Harwood, Jennifer Wozencraft

Periodical inspection and maintenance of critical infrastructure such as dams, penstocks, and locks are of significant importance to prevent catastrophic failures.

Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

no code implementations6 Dec 2017 Kartik Mohta, Michael Watterson, Yash Mulgaonkar, Sikang Liu, Chao Qu, Anurag Makineni, Kelsey Saulnier, Ke Sun, Alex Zhu, Jeffrey Delmerico, Konstantinos Karydis, Nikolay Atanasov, Giuseppe Loianno, Davide Scaramuzza, Kostas Daniilidis, Camillo Jose Taylor, Vijay Kumar

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment.


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