Mr. Fabio Vulpi Profile

Fabio Vulpi

at Sistemi e Tecnologie Industriali Intelligenti per il Manifattuier

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 20 June 2021 Presentation + Paper

Learning and prediction of vehicle-terrain interaction from 3D vision

Angelo Ugenti, Fabio Vulpi, Annalisa Milella, Giulio Reina

Proceedings Volume 11785, 117850T (2021) https://doi.org/10.1117/12.2596021

Read Abstract +

Wheel-terrain interaction plays a critical role for vehicle mobility on natural terrain, such as in agricultural, planetary exploration and off-road settings. Estimation of the terrain characteristics and the way they affect traversability is essential for the vehicle to better plan its safest and energy-efficient path. This work proposes a novel approach to learn and predict from a distance the motion resistance encountered by a robotic vehicle, while traversing natural soil, by using visual information from a stereovision device. To this end, terrain appearance and geometry information are first correlated to resistance torque measurements during a learning phase via two alternative regression approaches, namely Least-Squares Boosting and Long-Short Term Memory Recurrent Neural Network. Then, such a relationship is exploited to predict motion resistance remotely, based on visual data only. Results obtained in preliminary experimental tests on ploughed and compact terrain are presented to show the feasibility of the proposed method.

Proceedings Article | 20 June 2021 Paper

A self-calibration approach for multi-view RGB-D sensing

Antonio Petitti, Fabio Vulpi, Roberto Marani, Annalisa Milella

Proceedings Volume 11785, 117850C (2021) https://doi.org/10.1117/12.2595165

KEYWORDS: Cameras, Calibration, Sensors

Read Abstract +

In this paper, an approach for the estimation of relative positions and orientations of multiple rigidly coupled RGB-D sensors is presented. The proposed methodology does not impose constraints on the relative pose among the cameras, except for the rigidity: relative poses among cameras do not change in time. We assume that each camera captures an individual sequence which is afterward processed by a Simultaneous Localization And Mapping (SLAM) algorithm resulting in positions and orientations describing the trajectory followed by each sensor. Several simulations have been run considering a two-camera set having known input trajectories, affected by increasing levels of white noise. The results prove the capability of the algorithm in estimating the relative translations and rotations between the two cameras. Furthermore, experimental laboratory tests corroborate the effectiveness of the proposed method.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years