Michal Prauzek

About

Michal Prauzek is a robotics and autonomous systems researcher whose work spans mobile robot localization, scan matching algorithms, and applied robotics in challenging environments. His most significant contributions lie in developing innovative solutions for robot navigation and mapping, particularly within resource-constrained embedded systems. Prauzek's most cited work — a novel point-to-point scan matching algorithm based on cross-correlation (2016, 20 citations) — represents a meaningful advance in mobile robot localization for both indoor and outdoor settings. This research laid the foundation for several follow-on studies, including SLAM implementations, differential evolution-based scan matching, and ICP algorithm optimization for embedded platforms, forming a cohesive body of work addressing the persistent challenge of accurate, computationally efficient robot positioning. Beyond localization, Prauzek has demonstrated a talent for translating robotics research into real-world applications, notably developing a mobile robot designed to explore hazardous waste rock sites and detect toxic gases — work that underscores his commitment to socially relevant engineering. More recently, his research has extended to robotic manipulator calibration using advanced industrial camera models (2024, 8 citations), reflecting continued growth into precision robotics. With over 50 cumulative citations, his contributions offer valuable insights for researchers working at the intersection of autonomous navigation, embedded computing, and applied robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Novel Point-to-Point Scan Matching Algorithm Based on Cross-Correlation

   20 citations · 2016
2. 2
   Advanced Waste Rock Exploring by Mobile Robot

   11 citations · 2013
3. 3
   Industrial camera model positioned on an effector for automated tool center point calibration

   8 citations · 2024
4. 4
   ICP Algorithm in Mobile Robot Navigation: Analysis of Computational Demands in Embedded Solutions**This work was supported by the project SP2016/162, Development of algorithms and systems for control, measurement and safety applications II of Student Grant System, VSB-TU Ostrava.

   7 citations · 2016
5. 5
   Point-Based Scan Matching by Differential Evolution

   6 citations · 2016
6. 6
   Implementation of Orienteering Methods for Advanced Autonomous Robot

   2 citations · 2013
7. 7
   Indoor LiDAR Scan Matching Simulation Framework for Intelligent Algorithms Evaluation

   2 citations · 2016
8. 8
   SLAM Algorithm Based on Cross-Correlation Scan Matching

   2 citations · 2016
9. 9
   Scan Matching Cross-Correlation-Based Localization Algorithm: Embedded Systems Implementation Perspective

   1 citations · 2018

Key Collaborators

Contact & Links