Martin L. Leuschen
Papers
11
Total Citations
164
H-Index
7
About
Martin L. Leuschen is a leading researcher in fault detection and reliability engineering for robotic systems operating in hazardous environments. His work centers on extending analytical redundancy (AR) techniques—traditionally limited to linear systems—into the nonlinear domain, enabling robust fault detection for complex, real-world robots. Leuschen’s most influential paper, "Fault residual generation via nonlinear analytical redundancy" (2005), with 59 citations, formalizes this breakthrough by exploiting nonlinear geometric control theory to generate fault detection tests. He applied these methods to hydraulic robots like the Rosie mobile worksystem, designed for nuclear reactor decontamination and dismantlement, demonstrating practical reliability improvements in high-stakes settings. His research also integrates fuzzy logic and Markov models to assess robot reliability under uncertainty, as seen in works like "Robot reliability using fuzzy fault trees and Markov models" (1996). With over 160 total citations across his top papers, Leuschen’s contributions are pivotal for ensuring the safety and dependability of robots in nuclear, hazardous, and unstructured environments, making his work essential reading for engineers and researchers in robotics and control systems.
Research Focus
Key Achievements
Top Papers
- 1Fault residual generation via nonlinear analytical redundancy59 citations · 2005
- 2Robotic fault detection using nonlinear analytical redundancy22 citations · 2003
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- 5Evaluating the reliability of prototype degradable systems10 citations · 2001
- 6Nonlinear Fault Detection for Hydraulic Systems8 citations · 2007
- 7Experimental AR Fault Detection Methods for a Hydraulic Robot7 citations · 2000
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- 9Robot reliability through fuzzy Markov models6 citations · 1998
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