Papers
9
Total Citations
257
H-Index
7
About
Majura F. Selekwa is a robotics and autonomous systems researcher whose career has been defined by solving some of the most persistent challenges in mobile robot navigation and control. His work spans fuzzy behavior-based control, terrain classification, path tracking, and simultaneous localization and mapping (SLAM), making him a versatile contributor to the field of unmanned ground vehicles (UGVs). Selekwa's most influential contribution, "Robot Navigation in Very Cluttered Environments by Preference-Based Fuzzy Behaviors" (2007), has accumulated over 100 citations and introduced an elegant framework for resolving behavioral conflicts in reactive navigation systems — a longstanding obstacle in autonomous robotics. His complementary work on virtual wall approaches to limit cycle avoidance further refined how UGVs handle complex obstacle configurations, earning 50 citations. Early work on online terrain classification (2005) addressed the real-world challenge of vehicles operating across unpredictable surfaces like sand and mud, while his 2011 research on four-wheel independently steered vehicles advanced precision path tracking for highly maneuverable platforms. With nearly 260 cumulative citations and contributions spanning over two decades — from foundational fuzzy control theory to modern SLAM methodologies — Selekwa represents a sustained and evolving voice in intelligent autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 3Online Terrain Classification for Mobile Robots32 citations · 2005
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- 7Centralized fuzzy behavior control for robot navigation8 citations · 2003
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