Concept

Drone

Publications associées (273)

Wearable and Self-Aware Machine Learning System for Online Cognitive Workload Monitoring and Drone Control

The use of robots in search and rescue is gaining particular interest, but singular skills are required to ensure efficient deployments in real missions. To face this problem, there is a need to develop more intuitive control interfaces. Moreover, to ensur ...

EPFL2020

Addressable Acoustic Actuation of 3D Printed Soft Robotic Microsystems

Mahmut Selman Sakar, Murat Kaynak, Pietro Luciano Jakobus Dirix

A design, manufacturing, and control methodology is presented for the transduction of ultrasound into frequency-selective actuation of multibody hydrogel mechanical systems. The modular design of compliant mechanisms is compatible with direct laser writing ...

2020

Drone-aided Localization in LoRa IoT Networks

Dario Floreano, Alexandru Rusu, Fabrizio Schiano, Giuseppe Cocco

Besides being part of the Internet of Things (IoT), drones can play a relevant role in it as enablers. The 3D mobility of UAVs can be exploited to improve node localization in IoT networks for, e.g., search and rescue or goods localization and tracking. On ...

2020

A Morphing Cargo Drone for Safe Flight in Proximity of Humans

Dario Floreano, Przemyslaw Mariusz Kornatowski, William John Stewart, Mir Alikhan Bin Mohammad Feroskhan

Delivery drones used by logistics companies today are equipped with unshielded propellers, which represent a major hurdle for in-hand parcel delivery. The exposed propeller blades are hazardous to unsuspecting bystanders, pets, and untrained users. One sol ...

2020

A predictive large neighborhood search for the dynamic electric autonomous dial-a-ride problem

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

The dynamic electric autonomous Dial-a-Ride Problem (e-ADARP) is a generalization ofthe dial-a-ride problem which employs electric Autonomous Vehicles (e-AVs) to provide sharedrides to on-line requests. The goal of the dynamic e-ADARP is to maximize the nu ...

2020

TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

Pascal Fua, Mateusz Kozinski, Leonardo Citraro, Subeesh Vasu

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

2020

Analysis of Pitot tube Airflow Velocity Sensor Behavior in Blockage Situations

Ata Jedari Golparvar

Several airplanes crashes throughout the past decades are linked to the failure of the airplane flow velocity sensor known as pitot device or pitot tube. The study of its behavior in blockage, either due to human errors or due to environmental factors, cou ...

IEEE2020

A Comparative Study of Collision Avoidance Algorithms for Unmanned Aerial Vehicles: Performance and Robustness to Noise

Denis Gillet, Alcherio Martinoli, Steven Adriaan Roelofsen

Over the past years, the field of small unmanned aerial vehicles has grown significantly and several applications have appeared, requiring always more autonomous flight. An important remaining challenge for fully autonomous unmanned aerial vehicles is coll ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Deep Drone Racing: From Simulation to Reality with Domain Randomization

Davide Scaramuzza

Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges for robotics, which still limit the deployment of small autonomous drones. We address these challenges in the context ...

2019

Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing

Davide Scaramuzza

Autonomous micro aerial vehicles still struggle with fast and agile maneuvers, dynamic environments, imperfect sensing, and state estimation drift. Autonomous drone racing brings these challenges to the fore. Human pilots can fly a previously unseen track ...

2019

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