Mr. Joshua D. Rubini Profile

Joshua D. Rubini

Lead Software Developer

SPIE Involvement:

Author

Publications (1)

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 | 3 May 2018 Paper

MAD-VR: machine learning, analysis, and design in virtual reality

J. Rubini

Proceedings Volume 10640, 1064008 (2018) https://doi.org/10.1117/12.2305020

KEYWORDS: Machine learning, Computer simulations, Sensors, Weapons, Monte Carlo methods, Artificial intelligence, Signal processing, Warfare

Read Abstract +

As the modern battlespace continues to evolve, reliance on relatively few, dominant weapon systems is rapidly becoming infeasible. New weapon systems must be able to communicate and coordinate with other actors in the mission arena to achieve warfighter objectives. This is creating an explosion of complexity and data/information processing burden that hampers the warfighter’s ability to effectively operate. This emerging complexity is in turn driving the need for sophisticated autonomous and semi-autonomous systems, as well as adaptive real-time filters and decision-assist mechanisms.

Machine learning, Analysis, and Design in Virtual Reality (MAD-VR) is a tool to facilitate the design, proof-of-concept, and initial testing of algorithms for autonomy, information fusion, and machine learning. Designed as a next-generation front-end for high-speed simulations, it specifically addresses the need for a high-level, system-of-systems environment within which to evaluate the battlespace impact of these critical algorithms. Engineers and technicians will be able to observe the execution of new control systems, sensor data, and decision support systems in a high-fidelity simulation incorporating a diverse breadth of weapons and platforms, all working together to achieve mission success. Additionally, the warfighter will be able to use this tool directly to help with mission planning and optimization, as a means of examining outcomes in a Monte Carlo style of analysis.

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