Jerry Jun Yokono
Papers
1
Total Citations
2
H-Index
1
About
Jerry Jun Yokono is a researcher at the forefront of vision-and-language manipulation, focusing on bridging the gap between human instructions and robotic action. His work tackles a fundamental challenge in human-robot interaction: the ambiguity inherent in natural language commands. In his most-cited paper, "Naming Objects for Vision-and-Language Manipulation" (2023), Yokono addresses how robots can develop a shared understanding of target objects with humans, even when instructions are incomplete or imprecisely phrased. By exploring how robots can resolve interpretation ambiguities—such as missing spatial cues or misnamed objects—he advances the reliability of robotic systems in real-world tasks. Though his citation count is still growing, his contributions are pivotal for making robots more intuitive and accessible, particularly in domestic and collaborative settings. Yokono’s work sits at the intersection of computer vision, natural language processing, and robotics, offering practical solutions for seamless human-robot communication. His research is essential reading for students and engineers aiming to build robots that truly understand and act on human intent.
Research Focus
Key Achievements
Top Papers
- 1Naming Objects for Vision-and-Language Manipulation2 citations · 2023