Papers
4
Total Citations
17
H-Index
3
About
Fujio Ikeda is a robotics researcher whose work bridges the gap between passive dynamics and human-robot interaction, with a particular focus on locomotion and sports training. His early contributions include a novel proposal for a right and left turning mechanism for quasi-passive walking robots (2015, 8 citations), addressing a key limitation in passive bipedal robots—their inability to navigate beyond straight-line walking. This work laid the foundation for more agile, energy-efficient walking machines. More recently, Ikeda has pioneered the concept of "self-coaching" using small, inexpensive humanoid robots for sports training. His 2016 paper on this method (4 citations) introduced a system where a target robot replicates a player's motion while a reference robot demonstrates an ideal form, allowing athletes to visually compare and correct their technique. Subsequent studies have explored posture memory retentivity (2018, 3 citations) and the specific application to forearm passes in volleyball (2017, 2 citations). Though his citation counts are modest, Ikeda’s work is notable for its originality in merging robotics with sports science, offering a low-cost, interactive training tool that empowers athletes to coach themselves.
Research Focus
Key Achievements
Top Papers
- 1
- 2Sports Training Support Method by Self-Coaching with Humanoid Robot4 citations · 2016
- 3Evaluation of Posture Memory Retentivity using Coached Humanoid Robot3 citations · 2018
- 4Self-Coaching of Forearm Pass with Humanoid Robot2 citations · 2017