Marek Balazinski
Papers
9
Total Citations
125
H-Index
5
About
Marek Balazinski is a prominent researcher whose work sits at the intersection of robotics, intelligent control systems, and computational intelligence. His research has made significant contributions to trajectory planning, kinematic optimization, and the application of fuzzy logic and neural networks to robotic systems. Balazinski's most impactful work focuses on multi-objective trajectory planning for both serial and parallel kinematic machines, with his 2008 paper on constrained trajectory planning of parallel kinematic machines accumulating 55 citations — a testament to its influence in the field. His development of hierarchical neuro-fuzzy systems for near-optimal trajectory planning of redundant manipulators (31 citations) represents a particularly elegant fusion of machine learning and control theory, enabling robots to navigate complex motion constraints with greater efficiency. Beyond trajectory optimization, Balazinski has advanced methods for robotic system identification, applying Takagi-Sugeno-Kang fuzzy logic systems to model joint friction and rigid-body dynamics — notoriously difficult nonlinear phenomena. His work on fuzzy-based parking manoeuvres for non-holonomic wheeled mobile robots further demonstrates his versatility across robotic platforms. Collectively, his research provides foundational tools for designing smarter, more adaptive robotic systems, making his body of work an essential reference for researchers in intelligent robotics and autonomous motion planning.
Research Focus
Key Achievements
Top Papers
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- 4Fuzzy Parking Manoeuvres of Wheeled Mobile Robots8 citations · 2007
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