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Francisco J. Ruiz-Ruiz

dblp:289/4462 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-2763-4738ORCID · reported

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 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.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 50% Health and well-being technologies · 50%
Artificial intelligence
1 paper
Motion planning and robot control · 100%

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

TopicWeightPapersLastEvidence papers
Human-robot interaction › assistive robotics
physical assistance
0.612022
Improving Standing Balance Performance through the Assistance of a Mobile Collaborative Robot · ICRA 2022
Robotics › Motion planning and robot control › robot control
admittance control
0.212022
Improving Standing Balance Performance through the Assistance of a Mobile Collaborative Robot · ICRA 2022
Robotics › Motion planning and robot control
robot control
0.212022
Improving Standing Balance Performance through the Assistance of a Mobile Collaborative Robot · ICRA 2022

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

center of mass estimation · 1.1admittance control · 1.1
YearPublicationVenuePosition
2022 Improving Standing Balance Performance through the Assistance of a Mobile Collaborative Robot
abstract
This paper presents the design and development of a robotic system to give physical assistance to the elderly or people with neurological disorders such as Ataxia or Parkin-son's. In particular, we propose using a mobile collaborative robot with an interaction-assistive whole-body interface to help people unable to maintain balance. The robotic system consists of an Omni-directional mobile base, a high-payload robotic arm, and an admittance-type interface acting as a support handle while measuring human-sourced interaction forces. The postural balance of the human body is estimated through the projection of the body Center of Mass (CoM) to the support polygon (SP) representing the quasi-static Center of Pressure (CoP). In response to the interaction forces and the tracking of the human posture, the robot can create assistive forces to restore balance in case of its loss. Otherwise, during normal stance or walking, it will follow the user with minimum/no opposing forces through the generation of coupled arm and base movements. As the balance-restoring strategy, we propose two strategies and evaluate them in a laboratory setting on healthy human participants. Quantitative and qualitative results of a 12-subjects experiment are then illustrated and discussed, comparing the performances of the two strategies and the overall system.
Francisco J. Ruiz-Ruiz, Alberto Giammarino, Marta Lorenzini, Juan M. Gandarias, Jesús M. Gómez de Gabriel, Arash Ajoudani
ICRA1