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Antonio Alvarez Valdivia

dblp:305/7167 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › soft robotics
soft robot design
0.912025
Anisotropic Stiffness and Programmable Actuation for Soft Robots Enabled by an Inflated Rotational Joint · ICRA 2025

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

first-principle modeling · 0.9experimental characterization · 0.9
YearPublicationVenuePosition
2025 Anisotropic Stiffness and Programmable Actuation for Soft Robots Enabled by an Inflated Rotational Joint
abstract
Soft robots are known for their ability to perform tasks with great adaptability, enabled by their distributed, non-uniform stiffness and actuation. Bending is the most fundamental motion for soft robot design, but creating robust, and easy-to-fabricate soft bending joint with tunable properties remains an active problem of research. In this work, we demonstrate an inflatable actuation module for soft robots with a defined bending plane enabled by forced partial wrinkling. This lowers the structural stiffness in the bending direction, with the final stiffness easily designed by the ratio of wrinkled and unwrinkled regions. We show the stiffness properties of the actuation module through a first-principle model validated by experimental characterization, and demonstrate the module's ability to maintain the kinematic constraint over a large range of loading conditions. We illustrate how these properties give the potential for complex actuation in a soft continuum robot and for decoupling actuation force and efficiency from load capacity. The module provides a novel method for embedding intelligent actuation into soft pneumatic robots.
Sicheng Wang 0002, Eugenio Frias Miranda, Antonio Alvarez Valdivia, Laura H. Blumenschein
ICRA3