Piotr Gierlak

About

Piotr Gierlak is a prominent robotics researcher whose work spans industrial robot programming, adaptive force control, and intelligent manufacturing systems. Based at the intersection of classical robotics and emerging digital technologies, his research has made significant contributions to how industrial robots are programmed, controlled, and monitored in real-world environments. Gierlak's most impactful work, "Programming of Industrial Robots Using Virtual Reality and Digital Twins" (2020, 110 citations), pioneered an innovative approach to robot programming by capturing human movements within virtual environments that mirror physical robotic stations. This contribution arrived at a critical moment in Industry 4.0 adoption. His earlier foundational research established robust frameworks for adaptive position/force control of manipulators interacting with flexible environments (71 citations), while parallel work on vibration-based tool condition monitoring (53 citations) addressed practical manufacturing reliability challenges. His application of neural networks and fuzzy logic to hybrid position/force control during robotic machining demonstrates a consistent drive toward intelligent, adaptive systems. More recently, his work on robotic grinding of turboprop engine compressor blades and laser tracker-based robot programming reflects a broadening scope toward precision aerospace manufacturing. Collectively, Gierlak's portfolio represents a coherent vision of smarter, more adaptive, and more intuitively programmable industrial robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Programming of Industrial Robots Using Virtual Reality and Digital Twins

   110 citations · 2020
2. 2
   Adaptive position/force control for robot manipulator in contact with a flexible environment

   71 citations · 2017
3. 3
   On-line manipulator tool condition monitoring based on vibration analysis

   53 citations · 2016
4. 4
   Application of Virtual Reality in the Training of Operators and Servicing of Robotic Stations

   22 citations · 2019
5. 5
   Hybrid Position/Force Control in Robotised Machining

   20 citations · 2013
6. 6
   Programming of Industrial Robots Using a Laser Tracker

   19 citations · 2022
7. 7
   Robotic Grinding Process of Turboprop Engine Compressor Blades with Active Selection of Contact Force

   18 citations · 2021
8. 8
   Adaptive Position/Force Control of a Robotic Manipulator in Contact with a Flexible and Uncertain Environment

   17 citations · 2021
9. 9
   Hybrid Position/Force Control of the SCORBOT-ER 4pc Manipulator with Neural Compensation of Nonlinearities

   15 citations · 2012
10. 10
    Conventional and Fuzzy Force Control in Robotised Machining

    14 citations · 2013

Key Collaborators

Contact & Links