Ololade O Obadina

Queen Mary University of London

Papers

3

Total Citations

68

H-Index

3

About

Ololade O. Obadina is a robotics researcher whose work centers on the dynamic modeling and intelligent control of robotic manipulator systems, particularly master–slave and leader–follower configurations. His major contributions lie in developing hybrid optimization algorithms—most notably the grey wolf–whale optimization algorithm—that significantly improve the accuracy of parametric modeling for complex robotic systems. He has also advanced grey-box modeling techniques and fuzzy logic control strategies for real-time trajectory control, as demonstrated in his highly cited 2021 and 2022 papers, which together have accumulated over 59 citations. Obadina’s 2018 work on a modified computed torque control approach further showcases his expertise in robust control design. His research is notable for bridging classical control theory with modern bio-inspired optimization, offering practical solutions for precision manipulation tasks. With a growing citation record and a focus on experimentally validated systems, Obadina is establishing himself as a rising voice in the field of robotic control and optimization.

Research Focus

Key Achievements

3
H-Index
3
Papers
68
Total Citations
23
Avg Citations/Paper
🏆 Most Cited Paper
Dynamic characterization of a master–slave robotic manipulator using a hybrid grey wolf–whale optimization algorithm
33 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Queen Mary University of London

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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