Mark White
Papers
8
Total Citations
98
H-Index
5
About
Mark White is a robotics and artificial intelligence researcher whose work has made meaningful contributions to the field of autonomous mobile robotics, particularly in the areas of robot self-localization, neural network-based mapping, and evolutionary robotics. His most influential contribution, "Autonomous Mobile Robot Global Self-Localization Using Kohonen and Region-Feature Neural Networks" (1997), has garnered 45 citations and introduced two distinct neural network architectures for solving the challenging problem of global self-localization (GSL) — enabling robots to determine their position within an environment without prior pose knowledge. White's sustained focus on this problem led to a productive body of work in 2002, exploring Kohonen self-organizing networks, hyper-ellipsoid clustering, and the region-feature neural network (RFNN), including pioneering research into multi-robot knowledge sharing between physically distinct robotic platforms. His 2004 paper on evolutionary robotics further demonstrated his breadth, applying competitive fitness selection to evolve complex autonomous behaviors. With a cumulative citation count approaching 100 across his publications, White's research offers foundational insights for students and researchers working at the intersection of machine learning, sensor fusion, and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 3Evolution of complex autonomous robot behaviors using competitive fitness12 citations · 2004
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