96 citations · 136 across the 10 of their papers we have counts for
10 papers
Resource-Aware Collaborative Monte Carlo Localization with Distribution Compression
Nicky Zimmerman, Alessandro Giusti, Jérôme Guzzi
Global localization is essential in enabling robot autonomy, and collaborative localization is key for multi-robot systems. In this paper, we address the task of collaborative glob…
Challenges in Visual Anomaly Detection for Mobile Robots
Dario Mantegazza, Alessandro Giusti, Luca M. Gambardella +2
We consider the task of detecting anomalies for autonomous mobile robots based on vision. We categorize relevant types of visual anomalies and discuss how they can be detected by u…
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots
Dario Mantegazza, Alessandro Giusti, Luca Maria Gambardella +1
We consider the problem of building visual anomaly detection systems for mobile robots. Standard anomaly detection models are trained using large datasets composed only of non-anom…
Training Lightweight CNNs for Human-Nanodrone Proximity Interaction from Small Datasets using Background Randomization
Marco Ferri, Dario Mantegazza, Elia Cereda +5
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 synth…
Sensing Anomalies as Potential Hazards: Datasets and Benchmarks
Dario Mantegazza, Carlos Redondo, Fran Espada +3
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 robo…
Fully Onboard AI-powered Human-Drone Pose Estimation on Ultra-low Power Autonomous Flying Nano-UAVs
Daniele Palossi, Nicky Zimmerman, Alessio Burrello +6
Artificial intelligence-powered pocket-sized air robots have the potential to revolutionize the Internet-of-Things ecosystem, acting as autonomous, unobtrusive, and ubiquitous smar…
Uncertainty-Aware Self-Supervised Learning of Spatial Perception Tasks
Mirko Nava, Antonio Paolillo, Jérôme Guzzi +2
We propose a general self-supervised learning approach for spatial perception tasks, such as estimating the pose of an object relative to the robot, from onboard sensor readings. T…
Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches
Dario Mantegazza, Jérôme Guzzi, Luca M. Gambardella +1
We consider the task of controlling a quadrotor to hover in front of a freely moving user, using input data from an onboard camera. On this specific task we compare two widespread…
Learning Long-Range Perception Using Self-Supervision from Short-Range Sensors and Odometry
Mirko Nava, Jerome Guzzi, R. Omar Chavez-Garcia +2
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…
Learning Ground Traversability from Simulations
R. Omar Chavez-Garcia, Jerome Guzzi, Luca M. Gambardella +1
Mobile ground robots operating on unstructured terrain must predict which areas of the environment they are able to pass in order to plan feasible paths. We address traversability…