Robert K. McConnell

Color (United States)

Papers

2

Total Citations

4

H-Index

2

About

Robert K. McConnell is a pioneering researcher in the field of color and multispectral machine vision, with a focus on robust object recognition for mobile robotics. His major contributions center on developing off-the-shelf systems that can be quickly trained by example to recognize objects with complex color mixtures and textures, moving beyond traditional single-color, simple-outline models. This work addresses a critical challenge: enabling robots to operate effectively in unstructured, real-world environments where lighting and object appearances are unpredictable. McConnell's most-cited papers, including "When trees are not green" (2009) and "Off-the-shelf system for color and multispectral based recognition and control" (2008), have each garnered 2 citations, laying foundational groundwork for adaptive, example-based recognition systems. His research is particularly notable for its practical, deployable approach—making sophisticated multispectral analysis accessible for robot control without requiring specialized hardware. For students and researchers in robotics and computer vision, McConnell's work offers a pragmatic bridge between theoretical color models and real-world robotic perception, demonstrating how robust, trainable systems can transform how machines interact with their environments.

Research Focus

Key Achievements

2
H-Index
2
Papers
4
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
When trees are not green: Recent developments in an off-the-shelf system for robust color and multispectral based recognition and robot control
2 citations · 2009
📈 Most Prolific Year: 2009 (1 Papers)
🤝 Key Collaborators: 0
🏛 Institutions: Color (United States)

Top Papers

  1. 1
  2. 2

Contact & Links

Available for collaboration
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