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Gloria Peinado

dblp:43/9968 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 91% Health and well-being technologies · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › adaptive robot behavior
adaptive assistance
0.112011
Navigation skills based profiling for collaborative wheelchair control · ICRA 2011
Human-robot interaction
assistive robotics
0.112011
Navigation skills based profiling for collaborative wheelchair control · ICRA 2011
Human-robot interaction
shared control
0.112011
Navigation skills based profiling for collaborative wheelchair control · ICRA 2011

Methods — techniques the papers use, named apart from their topics

driver profiling · 0.1clustering · 0.1
YearPublicationVenuePosition
2011 Navigation skills based profiling for collaborative wheelchair control
abstract
This work presents a new approach to proactive collaborative wheelchair control. The system is based on estimating how much help the person needs at each situation and providing just the correct amount. This is achieved by combining robot and human control commands in a reactive fashion after weighting them by their respective local efficiency. Thus, the better the person drives, the more control he/she is awarded with. In order to predict how much help users may need in advance rather than waiting for them to decrease in efficiency, their skills to deal with each situation are estimated with respect to a baseline driver profile to increase assistance when needed. Situations are characterized at reactive level to keep a reduced set. This profile has been extracted from real traces of more than 70 inpatients presenting different physical and cognitive skills via clustering. The approach has been successfully tested at Fondazione Santa Lucia (FSL) in Rome.
Gloria Peinado, Cristina Urdiales, Jose Manuel Peula, Manuel Fernández-Carmona, Roberta Annicchiarico, Francisco Sandoval 0001, Carlo Caltagirone
ICRA1