Francisco Yumbla
Escuela Superior Politecnica del Litoral, Sungkyunkwan University
Papers
21
Total Citations
212
H-Index
8
About
Francisco Yumbla is a robotics researcher whose work bridges the critical gap between industrial automation and intelligent manipulation. His primary research areas include wire harness assembly automation, cable connector mating, collaborative robotics, and task and motion planning. Yumbla’s most significant contributions lie in solving the notoriously difficult problem of automated cable connector mating—a task requiring precise tolerance analysis, recognition, and passive alignment strategies. His 2019 paper on the tolerance dataset for plug-in cable connectors (29 citations) and his 2020 work on connector recognition using image processing (26 citations) have become foundational references in this niche. He also made notable advances in robot control, proposing a passivity-guaranteed dynamic friction model that accounts for temperature and load (20 citations), and developing a combined task and motion planning framework using primitive actions (17 citations). Yumbla’s work on online task planning with mixed integer programming for dual-arm cooking robots (16 citations) demonstrates his versatility in service robotics. His recent open-source multi-robot framework based on ROS2 (2025) signals his ongoing commitment to collaborative robotics interoperability. With over 165 total citations across his ten most-cited papers, Yumbla is establishing himself as a key contributor to the practical challenges of industrial and service robot manipulation.
Research Focus
Key Achievements
Top Papers
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