Ai Tateishi
Papers
2
Total Citations
10
H-Index
2
About
Ai Tateishi is a pioneering researcher in robotic manipulation, with a focus on enabling robots to perform complex, real-world tasks that require dexterous handling of both rigid and deformable objects. Her key research areas include dual-arm robotic systems, task learning from demonstrations, and motor babbling for skill acquisition. In her landmark 2022 study, Tateishi conducted the first-ever trial of a robotic buttoning task using a dual-arm robot, a challenge previously considered too complex due to the simultaneous manipulation of flexible clothing and solid buttons. This work, cited 7 times, introduced both marker-based algorithmic methods and marker-less machine learning approaches, setting a new benchmark for fine-grained manipulation. She has also advanced robot task learning with her work on motor babbling using pseudo rehearsal, which reduces the costly need for human demonstrations by allowing robots to autonomously explore and acquire motor skills through random movement. With 10 total citations, Tateishi’s contributions are shaping the future of assistive robotics and autonomous garment handling, demonstrating that robots can master intricate, human-like tasks with innovative learning strategies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robot Task Learning With Motor Babbling Using Pseudo Rehearsal3 citations · 2022