Papers
7
Total Citations
102
H-Index
5
About
Yong-Ho Yoo is a pioneering researcher in the field of robotic task intelligence, with a focus on endowing robots with human-like cognitive capabilities. His work centers on developing biologically inspired neural models for episodic and procedural memory, enabling robots to autonomously perform complex, sequential tasks. Yoo’s major contributions include the creation of the Deep ART neural model for episodic memory, which allows robots to store and retrieve temporal event sequences, and a neural model-based mechanism of thought for online motion planning. His most cited papers, such as "Task Intelligence of Robots" and "Deep ART Neural Model," each with 33 citations, have laid the groundwork for robots to reason, learn from demonstration, and execute tasks in dynamic environments. Yoo has also explored extraterrestrial robotics, developing virtual environments for lunar crater exploration. His integrated approach to memory and task performance represents a significant leap toward truly intelligent autonomous systems, making his work essential reading for students and researchers in cognitive robotics and artificial intelligence.
Research Focus
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Top Papers
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- 3Procedural Memory Learning from Demonstration for Task Performance16 citations · 2015
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