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Rafael Herguedas

dblp:249/3063 · DBLP profile ↗
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2ranked-venue papers
2as first author
1since 2021 · last 2022
0000-0001-9642-7655ORCID · corroborated

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

Systems, architecture and hardware · 2 · 2 first-author · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 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
Motion planning and robot control · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › safe control
control barrier functions
0.612022
Multirobot control with double-integrator dynamics and control barrier functions for deformable object transport · ICRA 2022
Robotics › Motion planning and robot control › multi-robot control
multi-robot formation control
0.612022
Multirobot control with double-integrator dynamics and control barrier functions for deformable object transport · ICRA 2022

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

double-integrator dynamics · 0.6control barrier functions · 0.6
YearPublicationVenuePosition
2022 Multirobot control with double-integrator dynamics and control barrier functions for deformable object transport
abstract
In this paper, we propose a formation control system for deforming and transporting simultaneously a de-formable object with a team of robots, modeled with double-integrator dynamics. The goal is to reach a target configuration, defined as a combination of shape, scale, orientation and position of the formation. We augment this controller with a set of control barrier functions (CBFs). The CBFs allow us to satisfy fundamental constraints for the success of the task: avoidance of agent-to-agent, agent-to-obstacle and object-to-obstacle collisions, and of excessive stretching. We test the performance of our proposal in different simulation scenarios.
Rafael Herguedas, Miguel Aranda, Gonzalo López-Nicolás, Carlos Sagüés, Youcef Mezouar
ICRA1
2019 Survey on multi-robot manipulation of deformable objects
abstract
Autonomous manipulation of deformable objects is a research topic of increasing interest due to the variety of current processes and applications that include this type of tasks. It is a complex problem that involves aspects such as modeling, control, perception, planning, grasping, estimation, etc. A single robot may be unable to perform the manipulation when the deformable object is too big, too heavy or difficult to grasp. Then, using multiple robots working together naturally arises as a solution to perform coordinately the manipulation task. In this paper, we contribute a survey of relevant state-of-the-art approaches concerning manipulation of deformable objects by multiple robots, which includes a specific classification with different criteria and a subsequent analysis of the leading methods, the main challenges and the future research directions.
Rafael Herguedas, Gonzalo López-Nicolás, Rosario Aragues, Carlos Sagüés
ETFA1