Marina Murillo

Papers

1

Total Citations

39

H-Index

1

About

Marina Murillo is a researcher whose work sits at the intersection of robotics, autonomous systems, and vehicle dynamics, with a particular focus on the motion planning and control of complex mechanical systems. Her most notable contribution to date is her 2022 paper, "Improving Path-Tracking Performance of an Articulated Tractor-Trailer System Using a Non-Linear Kinematic Model," which has garnered 39 citations — a strong indicator of early impact in a specialized and technically demanding field. In this work, Murillo addresses one of the persistent challenges in autonomous ground vehicle research: achieving precise path-tracking for articulated vehicles, which are notoriously difficult to control due to their multi-body kinematics and susceptibility to jackknifing and off-tracking errors. By incorporating a non-linear kinematic model, she demonstrated measurable improvements in tracking accuracy over conventional approaches, offering practical insights applicable to agricultural robotics, autonomous logistics, and heavy vehicle automation. Her research reflects a broader commitment to bridging theoretical modeling with real-world performance, making her contributions particularly valuable for engineers and scientists working on next-generation autonomous transportation systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
39
Total Citations
39
Avg Citations/Paper
🏆 Most Cited Paper
Improving path-tracking performance of an articulated tractor-trailer system using a non-linear kinematic model
39 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago