8 citations · 10 across the 2 of their papers we have counts for
6 papers
Semantic constraints to represent common sense required in household actions for multi-modal Learning-from-observation robot
Katsushi Ikeuchi, Naoki Wake, Riku Arakawa +2
The paradigm of learning-from-observation (LfO) enables a robot to learn how to perform actions by observing human-demonstrated actions. Previous research in LfO have mainly focuse…
Understanding Action Sequences based on Video Captioning for Learning-from-Observation
Iori Yanokura, Naoki Wake, Kazuhiro Sasabuchi +2
Learning actions from human demonstration video is promising for intelligent robotic systems. Extracting the exact section and re-observing the extracted video section in detail is…
Grasp-type Recognition Leveraging Object Affordance
Naoki Wake, Kazuhiro Sasabuchi, Katsushi Ikeuchi
A key challenge in robot teaching is grasp-type recognition with a single RGB image and a target object name. Here, we propose a simple yet effective pipeline to enhance learning-b…
A Learning-from-Observation Framework: One-Shot Robot Teaching for Grasp-Manipulation-Release Household Operations
Naoki Wake, Riku Arakawa, Iori Yanokura +4
A household robot is expected to perform various manipulative operations with an understanding of the purpose of the task. To this end, a desirable robotic application should provi…
Task-oriented Motion Mapping on Robots of Various Configuration using Body Role Division
Kazuhiro Sasabuchi, Naoki Wake, Katsushi Ikeuchi
Many works in robot teaching either focus only on teaching task knowledge, such as geometric constraints, or motion knowledge, such as the motion for accomplishing a task. However,…
Verbal Focus-of-Attention System for Learning-from-Observation
Naoki Wake, Iori Yanokura, Kazuhiro Sasabuchi +1
The learning-from-observation (LfO) framework aims to map human demonstrations to a robot to reduce programming effort. To this end, an LfO system encodes a human demonstration int…