Tatiana Kalganova

Brunel University of London

Papers

10

Total Citations

50

H-Index

5

About

Tatiana Kalganova is a robotics and intelligent systems researcher whose work centers on two primary domains: ambidextrous robotic systems and evolvable hardware. She is perhaps best known for pioneering the design and control of ambidextrous robotic hands and arms — devices capable of performing both left- and right-hand movements, effectively doubling the range of motion compared to conventional dexterous limbs. Her early contributions established the mechanical foundations of low-cost 3D-printed ambidextrous fingers and hands actuated by pneumatic artificial muscles, making advanced prosthetic and industrial robotics more accessible and versatile. Building on this hardware innovation, Kalganova has progressively advanced the intelligence behind these systems, incorporating neural networks, Multiple Adaptive Neuro-Fuzzy Inference Systems (MANFIS), PID, bang–bang, and backstepping controllers to achieve precise, adaptive motion control. Her most cited work (2021, 12 citations) demonstrates a sophisticated control architecture for an ambidextrous arm combining pneumatic and electric actuation. Beyond robotics, her earlier research in evolvable hardware explored mutation rate optimization for evolutionary circuit design. Across her portfolio, Kalganova's research reflects a consistent commitment to bridging mechanical innovation with intelligent control, with particular relevance to biomedical robotics and tele-operation applications.

Research Focus

Key Achievements

5
H-Index
10
Papers
50
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A control structure for ambidextrous robot arm based on Multiple Adaptive Neuro‐Fuzzy Inference System
12 citations · 2021
📈 Most Prolific Year: 2015 (2 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Brunel University of London

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago