Ian Perera
Papers
2
Total Citations
27
H-Index
2
About
Ian Perera is a researcher in human-robot interaction and natural language processing, with a focus on enabling flexible, continuous communication between humans and autonomous systems. His most influential work, "Make it So: Continuous, Flexible Natural Language Interaction with an Autonomous Robot" (2012, 24 citations), addresses the challenge of moving beyond constrained command-based robot control to create fully autonomous agents that can engage in rich, ongoing dialogue with operators. This work demonstrates how robots can interpret and act on natural language in dynamic environments, bridging the gap between linguistic understanding and autonomous decision-making. Perera also explores how language comprehension systems can handle ambiguity in visually-grounded contexts, as shown in his 2015 study on cross-situational learning (3 citations), which reveals that humans use pragmatic cues like quantity and contrast to resolve referential uncertainty. His contributions advance the development of more intuitive human-robot collaboration, where language serves as a natural interface for complex tasks. By tackling the interplay between linguistic convention and contextual reasoning, Perera’s research lays groundwork for robots that truly understand and respond to human communication in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2