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Rizzi Galibut

dblp:387/7898 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

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.

Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 61% Human-robot interaction · 30% Health and well-being technologies · 9%

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

TopicWeightPapersLastEvidence papers
Haptics and multimodal interaction › haptic feedback
force feedback
0.912025
Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions · ICRA 2025
Haptics and multimodal interaction
haptic interface
0.912025
Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions · ICRA 2025
Human-robot interaction
physical human-robot interaction
0.912025
Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions · ICRA 2025
Health and well-being technologies › rehabilitation
physical therapy
0.312025
Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions · ICRA 2025

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

biomechanical modeling · 0.9CAD design · 0.9
YearPublicationVenuePosition
2025 Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions
abstract
Human-robot physical interaction (pHRI) is a rapidly evolving research field with significant implications for physical therapy, search and rescue, and telemedicine. However, a major challenge lies in accurately understanding human constraints and safety in human-robot physical experiments without an IRB and physical human experiments. Concerns regarding human studies include safety concerns, repeatabil-ity, scalability of the number, and diversity of participants. This paper examines whether a physical approximation can serve as a stand-in for human subjects to enhance robot autonomy for physical assistance. This paper introduces the SHULDRD (Shoulder Haptic Universal Limb Dynamic Repositioning Device), an economical and anatomically similar device designed for real-time testing and deploying pHRI planning tasks on robots in the real world. SHULDRD replicates human shoulder motion, providing crucial force feedback and safety data. The device's open-source CAD and software facilitate easy construction and use, ensuring broad accessibility for researchers. By providing a flexible platform able to emulate infinite human subjects, ensure repeatable trials, and provide quantitative metrics to assess the effectiveness of the robotic intervention, SHULDRD aims to improve the safety and efficacy of human-robot physical interactions. Project URL: https://sites.google.com/view/haptic-shoulder/home
Elizabeth Peiros, Calvin Joyce, Tarun Murugesan, Roger Nguyen, Isabella Fiorini, Rizzi Galibut, Michael C. Yip
ICRA6