Mitchell W Pryor
Biographic Data
| ID | 10123297 |
|---|---|
| NAME | Mitchell W Pryor |
| GIVEN NAMES | Mitchell W |
| FAMILY NAME | Pryor |
| SIGNATURE | PRYOR M W |
| AFFILIATIONS | The University of Texas at Austin |
| ORCID | 0000-0001-5089-9964 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
A Survey of Multimodal Perception Methods for Human–Robot Interaction in Social Environments
Human–robot interaction (HRI) in human social environments (HSEs) poses unique challenges for robot perception systems, which must combine asynchronous, heterogeneous data streams in real time. Multimodal perception systems are well-suited for HRI in HSEs and can provide more rich, robust interaction for robots operating among humans. In this article, we provide an overview of multimodal perception systems being used in HSEs, which is intended to…
Unified Meaning Representation Format (UMRF) - A Task Description and Execution Formalism for HRI
To facilitate continuous development of novel HRI systems, it is beneficial to have tools that enable quick adjustments, flexibility, or re-invention of the human interfaces when system requirements change due to updates in the state-of-the-art, application domain, etc. Thus, modularity is a key design principle which promotes software reuse and scalability, and reduces development time and cost. Hence, a robot’s autonomous capabilities should no…
No prominent works on this page.
Unified Meaning Representation Format (UMRF) - A Task Description and Execution Formalism for HRI
To facilitate continuous development of novel HRI systems, it is beneficial to have tools that enable quick adjustments, flexibility, or re-invention of the human interfaces when system requirements change due to updates in the state-of-the-art, application domain, etc. Thus, modularity is a key design principle which promotes software reuse and scalability, and reduces development time and cost. Hence, a robot’s autonomous capabilities should no…
A Survey of Multimodal Perception Methods for Human–Robot Interaction in Social Environments
Human–robot interaction (HRI) in human social environments (HSEs) poses unique challenges for robot perception systems, which must combine asynchronous, heterogeneous data streams in real time. Multimodal perception systems are well-suited for HRI in HSEs and can provide more rich, robust interaction for robots operating among humans. In this article, we provide an overview of multimodal perception systems being used in HSEs, which is intended to…
Artificial Intelligence (2 works) · Computer Science (2 works) · Human–computer interaction (2 works) · AI-based Problem Solving and Planning (1 work) · Cognitive psychology (1 work) · Human Pose and Action Recognition (1 work) · Human–robot interaction (1 work) · Mobile robot (1 work) · Multimodal Machine Learning Applications (1 work) · Neuroscience (1 work)