Michal Staniaszek
Papers
4
Total Citations
11
H-Index
2
About
Michal Staniaszek is a robotics researcher whose work focuses on planning under uncertainty for autonomous systems, with a particular emphasis on safety and long-term deployment in challenging environments. His key contributions lie in developing algorithms that enable robots to explore unknown spaces while guaranteeing safe operation, using Gaussian process prediction to model environmental conditions like terrain steepness or radiation levels. His 2024 paper on this topic has already garnered 5 citations, reflecting its timely relevance. Staniaszek also leads the development of AutoInspect, a ROS-based system for long-term autonomous industrial inspection, which has been successfully deployed in mines, chemical plants, decommissioned nuclear facilities, and a mock oil rig—demonstrating real-world impact. His work on difficulty-aware, time-bounded planning under uncertainty addresses large-scale missions where task durations are predictable but uncertain, modeled through Markov decision processes. With a total of 11 citations across his most-cited works, Staniaszek is advancing the frontier of safe, autonomous exploration and inspection, bridging theoretical planning with practical, high-stakes applications.
Research Focus
Key Achievements
Top Papers
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- 2AutoInspect: Towards Long-Term Autonomous Industrial Inspection3 citations · 2024
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