Search Results for author: Luca M. Gambardella

Found 9 papers, 4 papers with code

Training Lightweight CNNs for Human-Nanodrone Proximity Interaction from Small Datasets using Background Randomization

no code implementations27 Oct 2021 Marco Ferri, Dario Mantegazza, Elia Cereda, Nicky Zimmerman, Luca M. Gambardella, Daniele Palossi, Jérôme Guzzi, Alessandro Giusti

We consider the task of visually estimating the pose of a human from images acquired by a nearby nano-drone; in this context, we propose a data augmentation approach based on synthetic background substitution to learn a lightweight CNN model from a small real-world training set.

Data Augmentation

Sensing Anomalies as Potential Hazards: Datasets and Benchmarks

1 code implementation27 Oct 2021 Dario Mantegazza, Carlos Redondo, Fran Espada, Luca M. Gambardella, Alessandro Giusti, Jérôme Guzzi

We consider the problem of detecting, in the visual sensing data stream of an autonomous mobile robot, semantic patterns that are unusual (i. e., anomalous) with respect to the robot's previous experience in similar environments.

Anomaly Detection

Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches

1 code implementation24 Sep 2018 Dario Mantegazza, Jérôme Guzzi, Luca M. Gambardella, Alessandro Giusti

We consider the task of controlling a quadrotor to hover in front of a freely moving user, using input data from an onboard camera.

3D Human Pose Estimation

Learning Long-range Perception using Self-Supervision from Short-Range Sensors and Odometry

3 code implementations19 Sep 2018 Mirko Nava, Jerome Guzzi, R. Omar Chavez-Garcia, Luca M. Gambardella, Alessandro Giusti

We introduce a general self-supervised approach to predict the future outputs of a short-range sensor (such as a proximity sensor) given the current outputs of a long-range sensor (such as a camera); we assume that the former is directly related to some piece of information to be perceived (such as the presence of an obstacle in a given position), whereas the latter is information-rich but hard to interpret directly.


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