Papers
6
Total Citations
171
H-Index
5
About
Kohei Kikuchi is a leading researcher in industrial robotics, specializing in the automation of highly complex assembly tasks that have long resisted mechanization. His primary research areas include deformable part assembly, dual-arm mobile manipulation, and learning-based bin-picking. Kikuchi’s most influential work tackles one of the automotive industry’s toughest challenges: the robotized assembly of wire harnesses. His 2011 paper on this topic, with 79 citations, demonstrated a pioneering multi-robot-arm system that could handle flexible cables—a task previously requiring human dexterity. He further advanced this with a complete robot car wiring system (2008, 19 citations), addressing a critical bottleneck in vehicle production. Kikuchi also made key contributions to mobile manipulation, developing base-position planning algorithms for dual-arm robots performing pick-and-place sequences (2015, 20 citations). More recently, his experiments on learning-based industrial bin-picking (2018) combine random forest prediction with iterative visual recognition to enable robots to reliably grasp randomly stacked parts. By bridging classical robotics with machine learning, Kikuchi continues to push the boundaries of what industrial robots can achieve, directly impacting real-world manufacturing efficiency.
Research Focus
Key Achievements
Top Papers
- 1Robotized Assembly of a Wire Harness in a Car Production Line79 citations · 2011
- 2Robotized assembly of a wire harness in car production line42 citations · 2010
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- 4Development of a robot car wiring system19 citations · 2008
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