Maria Stachowiak
Papers
2
Total Citations
29
H-Index
2
About
Maria Stachowiak is a leading researcher in the automation and safety of mining infrastructure, with a primary focus on robotic inspection and intelligent sensing for underground environments. Her work centers on developing autonomous systems—particularly legged and wheeled robots—capable of navigating the harsh, confined spaces of deep mines to detect structural damage and classify operational terrain. Her most cited paper, "Procedures of Detecting Damage to a Conveyor Belt with Use of an Inspection Legged Robot for Deep Mine Infrastructure" (2021, 27 citations), introduces a novel methodology for using legged robots to identify critical belt wear in conveyor networks that can span hundreds of kilometers, directly addressing a key bottleneck in continuous horizontal transport. In related work, she explores terrain classification for wheeled robots using neural networks and inertial sensors, enhancing robot adaptability in unpredictable underground conditions. Stachowiak’s contributions are vital for reducing human risk in hazardous mining zones and improving the reliability of automated material handling. Her research bridges robotics, sensor fusion, and deep infrastructure monitoring, making her a notable figure in the push toward safer, more efficient mining operations.
Research Focus
Key Achievements
Top Papers
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- 2