Robin McDougall
Papers
3
Total Citations
19
H-Index
3
About
Robin McDougall is a researcher whose work sits at the intersection of robotics, probabilistic modeling, and nuclear safety. His primary research focus is on developing autonomous systems for radiation mapping, particularly in hazardous environments where human access is limited. McDougall’s major contribution lies in creating methodologies that allow mobile robots to generate accurate radiation intensity maps from sparse, noisy sensor data. His most-cited paper, "Probabilistic-Based Robotic Radiation Mapping Using Sparse Data" (2017, 11 citations), introduces a two-stage approach that integrates a radiation model with probabilistic analysis to produce reliable maps even with limited measurements. This work builds on his earlier foundational studies, including "A Mobile Robotic Platform for Generating Radiation Maps" (2012, 5 citations) and "Robotic radiation mapping using modelling and probabilistic analysis of sparse data" (2015, 3 citations), which together establish a framework for deploying robots in real-world scenarios like nuclear decommissioning or emergency response. While his citation counts are modest, his contributions are notable for their practical impact on field robotics and radiation safety, offering a scalable solution for monitoring contaminated zones. McDougall’s research is essential reading for students and engineers interested in autonomous environmental sensing and risk-aware robotics.
Research Focus
Key Achievements
Top Papers
- 1Probabilistic-Based Robotic Radiation Mapping Using Sparse Data11 citations · 2017
- 2A Mobile Robotic Platform for Generating Radiation Maps5 citations · 2012
- 3