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Saturday, 12 June 2004

ImageThis is the website of Ricardo Sanz, professor in systems engineering and automatic control and researcher in the field of autonomous systems.

In this site you will find information regarding my activitiy as well as other sources that may be of interest to you. Feel free to explore the site and to suggest any improvement to it.

I do most of my activity as part of the Autonomous Systems Laboratory. ASLab is a research group of ample interests ranging from conventional control and real-time systems to model-based engineering processes and artificial intelligence.

This last is, indeed, my main topic of interest; or to be more precise, I'm interested in mind theory, both artificial and natural within the long term engineering objective of systematically creating better machines by means of improving their intelligence.

Last Updated ( Saturday, 08 July 2017 )
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FFP Ética y Big Data
Sunday, 03 June 2018
Evento del Foro del Futuro Proximo sobre Ética y Tecnología. En esta sesión se debate sobre Ética y Big Data

Mas información en el Website del Foro del Futuro Proximo.

Last Updated ( Sunday, 03 June 2018 )
 
FFP 2017 Tecnología e Inmovilidad
Friday, 06 April 2018
A speech given at the FFP 2017.

A 3 minute version can be seen here

Last Updated ( Friday, 06 April 2018 )
 
A self-adaptation framework based on functional knowledge for augmented autonomy in robots
Thursday, 11 April 2013
Carlos Hernández, Julita Bermejo-Alonso and Ricardo Sanz
To appear in Integrated Computer-Aided Engineering
IOS Press through http://dx.doi.org/10.3233/ICA-180565

Robot control software endows robots with advanced capabilities for autonomous operation, such as navigation, object recognition or manipulation, in unstructured and dynamic environments. However, there is a steady need for more robust oper- ation, where robots should perform complex tasks by reliably exploiting these novel capabilities. Mission-level resilience is re- quired in the presence of component faults through failure recovery. To address this challenge, a novel self-adaptation framework based on functional knowledge for augmented autonomy is presented. A metacontroller is integrated on top of the robot control system, and it uses an explicit run-time model of the robot’s controller and its mission to adapt to operational changes. The model is grounded on a functional ontology that relates the robot’s mission with the robot’s architecture, and it is generated during the robot’s development from its engineering models. Advantages are discussed from both theoretical and practical viewpoints. An application example in a real autonomous mobile robot is provided. In this example, the generic metacontroller uses the robot’s functional model to adapt the control architecture to recover from a sensor failure.


A self-adaptation framework based on functional knowledge for augmented autonomy in robots. Carlos Hernández, Julita Bermejo-Alonso and Ricardo Sanz. Integrated Computer-Aided Engineering 2018, IOS Press

Article @ ASlab

Last Updated ( Thursday, 15 February 2018 )
 
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