About

Alexander Sherikov is a leading researcher in humanoid robotics, specializing in physical human-robot collaboration, walking motion generation, and whole-body control. His most impactful work, "Human-Humanoid Collaborative Carrying" (2019, 61 citations), introduces a complete control framework enabling humanoid robots to carry objects alongside humans, identifying primitive subtasks essential for safe, intuitive interaction. Sherikov has also made foundational contributions to model predictive control (MPC) for walking, with his 2011 paper comparing dense and sparse MPC formulations (33 and 31 citations) becoming a key reference for efficient motion generation. His research on safe navigation in crowds (32 citations) and walking pattern generators for physical collaboration (29 citations) further demonstrates his focus on deploying humanoids in dynamic, human-centric environments. Beyond collaborative carrying, Sherikov has advanced hierarchical task prioritization and contact force distribution for balance control, as seen in his 2015 work (13 citations). His 2015 IEEE TRO submission on resolving conflicting linear constraints (15 citations) highlights his expertise in optimization for robotics. With over 200 total citations, Sherikov’s work bridges theoretical control and practical human-robot interaction, making him a pivotal figure in creating robots that work safely alongside people.

Research Focus

Key Achievements

8
H-Index
11
Papers
240
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Human-Humanoid Collaborative Carrying
61 citations · 2019
📈 Most Prolific Year: 2016 (4 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Örebro University, Centre Inria de l'Université Grenoble Alpes, Institut national de recherche en sciences et technologies du numérique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago