Iordanis Chatzinikolaidis

University of Edinburgh

Papers

5

Total Citations

155

H-Index

5

About

Iordanis Chatzinikolaidis is a leading researcher in robotics, specializing in whole-body control, trajectory optimization, and human-robot collaboration. His work addresses fundamental challenges in enabling robots to operate autonomously and adaptively in complex, dynamic environments. A major contribution is the development of principled formalisms for dyadic collaborative manipulation (DcM), where robots must adapt to human partners in real time. His 2020 paper on "Online Hybrid Motion Planning for Dyadic Collaborative Manipulation via Bilevel Optimization" (53 citations) provides a groundbreaking framework for online joint planning. He also advanced automatic tuning for high-degree-of-freedom robots through Bayesian optimization, as detailed in his 2019 work (47 citations), which eliminates the need for laborious hand-tuning. Chatzinikolaidis further innovated contact-implicit trajectory optimization with an analytically solvable contact model (29 citations), enabling locomotion on variable ground. His work on automatic gait pattern selection for legged robots (13 citations) addresses the combinatorial complexity of locomotion planning. Collectively, his research has garnered over 150 citations, reflecting its significant impact on the fields of collaborative manipulation, legged locomotion, and autonomous robot control.

Research Focus

Key Achievements

5
H-Index
5
Papers
155
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
Online Hybrid Motion Planning for Dyadic Collaborative Manipulation via Bilevel Optimization
53 citations · 2020
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Edinburgh

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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