Derek T. Anderson
Papers
8
Total Citations
153
H-Index
6
About
Derek T. Anderson’s research bridges the gap between human intuition and autonomous systems, with a focus on sketch-based interfaces, robotics, and computer vision. His early work pioneered the use of hand-drawn sketches to control teams of mobile robots, demonstrating how qualitative maps and approximate positions could translate into actionable commands—a concept that remains influential in human-robot interaction. His 2004 paper on Hidden Markov Model symbol recognition for sketch-based interfaces (44 citations) tackled the core challenge of robust symbol recognition despite artistic variability, laying groundwork for intuitive design tools. More recently, Anderson has advanced deep learning for unmanned aerial vehicles (UAVs), developing photorealistic simulation frameworks (25 citations) that generate synthetic training data to overcome the “big data” barrier. His 2023 work on simulated gold-standards for monocular vision (8 citations) addresses the fundamental problem of obtaining ground truth in computer vision, proposing quantitative evaluation methods where physical truth is unattainable. Across his career, Anderson’s contributions—from fuzzy spatial relationship graphs for point clouds to stress-testing AI algorithms—have shaped how researchers train, evaluate, and deploy autonomous systems, with cumulative citations exceeding 150.
Research Focus
Key Achievements
Top Papers
- 1Using a hand-drawn sketch to control a team of robots50 citations · 2007
- 2Hidden Markov Model Symbol Recognition for Sketch-Based Interfaces.44 citations · 2004
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- 5Using a qualitative sketch to control a team of robots9 citations · 2006
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- 7Using a sketch pad interface for interacting with a robot team6 citations · 2005
- 8A Fuzzy Spatial Relationship Graph for Point Clouds Using Bounding Boxes2 citations · 2021