Cristian Tiriolo
Papers
5
Total Citations
48
H-Index
3
About
Cristian Tiriolo is an emerging robotics and control systems researcher whose work centers on mobile robot navigation, trajectory tracking, and autonomous control under constraints. His research makes significant contributions to the field of differential-drive robot control, with a particular focus on receding horizon (model predictive) control strategies combined with feedback linearization techniques. Tiriolo's most impactful contribution, garnering 27 citations, introduced a robust set-theoretic receding horizon scheme for input-constrained differential-drive robots, elegantly handling the challenging state-dependent input constraints inherent to these vehicles. Building on this foundation, he developed complementary set-theoretic control frameworks that address trajectory tracking through input-output linearization, accumulating an additional 12 citations. His earlier work on obstacle avoidance in unknown static environments demonstrated his ability to bridge theoretical control design with practical autonomous navigation challenges. More recently, Tiriolo has expanded his research scope toward multi-robot systems, proposing collision-free platooning strategies using set-theoretic predictive control — a promising direction for coordinated autonomous vehicle applications. Across his growing publication record, his work consistently bridges rigorous mathematical control theory with real-world robotic constraints, making his research highly relevant to engineers and researchers advancing autonomous mobile robotics.
Research Focus
Key Achievements
Top Papers
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