Mohammad Samin Yasar
Biographic Data
| ID | 10122939 |
|---|---|
| NAME | Mohammad Samin Yasar |
| GIVEN NAMES | Mohammad Samin |
| FAMILY NAME | Yasar |
| SIGNATURE | YASAR M S |
| AFFILIATIONS | University of Virginia |
| ORCID | 0000-0002-4684-2823 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A Holistic Evaluation of Teleoperation Interfaces for Robotic Manipulation
Robot teleoperation has become increasingly crucial for extending human capabilities in inaccessible or hazardous environments and facilitating human–robot collaboration. While significant advancements have been made in teleoperation interfaces, the success of these systems critically depends on how effectively humans can interact with and control robotic systems across diverse manipulation tasks. However, existing research primarily evaluates in…
Imprint: Interactional Dynamics-aware Motion Prediction in Teams using Multimodal Context
Robots are moving from working in isolation to working with humans as a part of human-robot teams. In such situations, they are expected to work with multiple humans and need to understand and predict the team members’ actions. To address this challenge, in this work, we introduce IMPRINT, a multi-agent motion prediction framework that models the interactional dynamics and incorporates the multimodal context (e.g., data from RGB and depth sensors…
No prominent works on this page.
Imprint: Interactional Dynamics-aware Motion Prediction in Teams using Multimodal Context
Robots are moving from working in isolation to working with humans as a part of human-robot teams. In such situations, they are expected to work with multiple humans and need to understand and predict the team members’ actions. To address this challenge, in this work, we introduce IMPRINT, a multi-agent motion prediction framework that models the interactional dynamics and incorporates the multimodal context (e.g., data from RGB and depth sensors…
A Holistic Evaluation of Teleoperation Interfaces for Robotic Manipulation
Robot teleoperation has become increasingly crucial for extending human capabilities in inaccessible or hazardous environments and facilitating human–robot collaboration. While significant advancements have been made in teleoperation interfaces, the success of these systems critically depends on how effectively humans can interact with and control robotic systems across diverse manipulation tasks. However, existing research primarily evaluates in…
Robot (2 works) · Action Observation and Synchronization (1 works) · Artificial Intelligence (1 works) · Cognitive Load (1 works) · Computer Science (1 works) · Human Motion and Animation (1 works) · Human Pose and Action Recognition (1 works) · Human-Automation Interaction and Safety (1 works) · Human–computer interaction (1 works) · Human–robot interaction (1 works)