Adi Sucipto
Papers
2
Total Citations
6
H-Index
2
About
Adi Sucipto is a robotics researcher focused on advancing bipedal locomotion and humanoid robot control, with particular emphasis on dynamic stability and real-world terrain adaptation. His most cited work, "Dynamic Stability Walking On Inclined Surface For 'T-FloW' Humanoid Robot Using Design Pattern Step" (2019, 4 citations), addresses a critical challenge in humanoid robotics: enabling stable, human-like walking on sloped surfaces. This research integrates mechanical system design with equilibrium motion control, proposing a design pattern step approach to maintain balance during incline traversal. Sucipto also contributes to the broader robotics community through his work on Robot Operating System (ROS) and RViz visualization tools, as demonstrated in his 2021 publication (2 citations), which explores interactive simulation for bipedal robot motion. While his citation counts reflect an emerging career, his focus on practical, control-oriented solutions for humanoid locomotion—particularly the intersection of mechanical design and real-time stability—positions him as a developing voice in the field. His work is especially relevant for researchers tackling the complexities of dynamic walking in unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 2