About

Hiromu Onda is a robotics researcher whose work centers on automating complex assembly and manipulation tasks, with a particular focus on pick-and-place operations, regrasp planning, and snap assembly. His major contributions include the development of a shape-adaptive gripper for robotic assembly, which has garnered 42 citations, and a regrasp planning component for object reorientation (40 citations). Onda’s object placement planner, validated in 2014, automatically determines stable poses for grasped objects, enabling more reliable pick-and-place tasks. He has also advanced assembly motion teaching systems using position/force simulators and virtual reality, allowing robots to learn from human demonstrations. Notably, Onda has pioneered work in snap-sensing and failure characterization for cantilever snap assemblies, developing hierarchical taxonomies to help robots detect and correct errors during assembly. His research on base position planning for dual-arm mobile manipulators further optimizes task sequences in industrial settings. With over 267 total citations across his top papers, Onda’s work bridges perception, planning, and control, making him a key figure in the push toward more autonomous and adaptable robotic assembly systems.

Research Focus

Key Achievements

11
H-Index
26
Papers
357
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Proposal of a shape adaptive gripper for robotic assembly tasks
42 citations · 2016
📈 Most Prolific Year: 2012 (4 Papers)
🤝 Key Collaborators: 38
🏛 Institutions: National Institute of Advanced Industrial Science and Technology, Sun Yat-sen University, Intelligent Systems Research (United States), Systems Research Institute

Top Papers

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    Towards snap sensing
    16 citations · 2013
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago