Papers
15
Total Citations
343
H-Index
8
About
Signe Redfield is a leading figure in the formalization of knowledge representation for robotics, whose work has fundamentally shaped how robots understand, reason about, and share information. Her primary research areas center on ontologies for robotics and automation, autonomous systems, and the standardization of robot task representation. Redfield’s most significant contribution is her leadership in developing the IEEE standard ontologies for robotics, including the foundational “IEEE Standard Ontologies for Robotics and Automation” (71 citations) and its critical extension for autonomous robotics (62 citations). These standards provide a formal, shared vocabulary and set of axioms that enable interoperability and communication between heterogeneous robotic systems, a cornerstone for advancing cloud robotics and multi-robot collaboration. With over 330 total citations, her work has established the formal backbone for the field. Notably, Redfield has also applied her expertise to pressing societal challenges, as seen in her recent work on telepresence robots for Long Covid, demonstrating a commitment to accessible, human-centered robotics. Her efforts in chairing the IEEE Robot Task Representation Study Group further underscore her role as a key architect of the conceptual frameworks that will drive the next generation of intelligent, autonomous machines.
Research Focus
Key Achievements
Top Papers
- 1IEEE Standard Ontologies for Robotics and Automation71 citations · 2015
- 2Extensions to the core ontology for robotics and automation65 citations · 2014
- 3Ontology for autonomous robotics62 citations · 2017
- 4A Suite of Ontologies for Robotics and Automation [Industrial Activities]53 citations · 2017
- 5Ontological concepts for information sharing in cloud robotics28 citations · 2020
- 6Towards a Robot Task Ontology Standard23 citations · 2017
- 7A definition for robotics as an academic discipline12 citations · 2019
- 8IEEE Standard for Autonomous Robotics (AuR) Ontology10 citations · 2021
- 9
- 10Lane finding using homogeneous groups of cooperating autonomous vehicles4 citations · 2004