Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Arrigo Croce

dblp:258/4479 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 · 100%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
animal-robot interaction
0.412020
Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica · IEEE Trans. Robotics 2020
Robotics › Robot manipulation › robot design
bio-inspired robot design
0.112020
Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica · IEEE Trans. Robotics 2020

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

feedback control · 0.9data-driven behavior modeling · 0.9
YearPublicationVenuePosition
2020 Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica
abstract
The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.
Pietro De Lellis, Edoardo Cadolini, Arrigo Croce, Yanpeng Yang, Mario di Bernardo, Maurizio Porfiri
IEEE Trans. Robotics3