Keisuke Takeshita
Keio University, Toyota Motor Corporation (Japan), Shinshu University
Papers
10
Total Citations
96
H-Index
6
About
Keisuke Takeshita is a roboticist advancing the frontier of autonomous manipulation for daily assistive and multi-robot systems. His research spans telexistence, deformable object handling, and cooperative transport—bridging perception, planning, and control. Takeshita’s most influential work, the TELESAR4 system (17 citations), introduced a mutual telexistence surrogate that enables remote participants to interact naturally via an autostereoscopic immersive display, redefining virtual presence. He has made pivotal contributions to robotic fabric manipulation, developing methods for a single-arm robot to pick up folded and stacked towels (16 citations) by estimating grasp positions from folded hems, ensuring shape reproducibility. His recent reinforcement learning framework for multi-robot task allocation (15 citations) enables decentralized agents to cooperatively transport objects with unknown weights, outperforming centralized approaches. Takeshita also pioneered door manipulation models integrating visual and tactile data (12 citations), reducing user instructions to a single click. His work on online motion generation using accumulated swept volumes (6 citations) and whole-body inverse kinematics for mobile manipulators (2 citations) demonstrates sustained impact in real-time motion planning. With over 90 combined citations, Takeshita’s research is foundational for robots that perceive, adapt, and collaborate in unstructured human environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Picking up One of the Folded and Stacked Towels by a Single Arm Robot16 citations · 2018
- 3
- 4A method of picking up a folded fabric product by a single-armed robot14 citations · 2018
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- 7Online motion generation using accumulated swept volumes6 citations · 2020
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