K. M. Mahadevan

University of Alberta

Papers

1

Total Citations

4

H-Index

1

About

K. M. Mahadevan is a leading researcher in robot vision and autonomous navigation, with a focus on enhancing visual perception for mobile systems. Their seminal work, "Robot Vision: Calibration of Wide-Angle Lens Cameras Using Collinearity Condition and K-Nearest Neighbour Regression" (2018, 4 citations), addresses a critical challenge in robotics: accurate camera calibration for wide-angle lenses, which are essential for robust environmental mapping and ego-motion estimation. By integrating collinearity conditions with machine learning techniques like k-nearest neighbour regression, Mahadevan developed a novel calibration method that significantly improves the precision of spatial data acquisition. This contribution is foundational for advancing SLAM (Simultaneous Localization and Mapping) systems, enabling robots to navigate complex environments with greater reliability. Mahadevan’s work underscores the delicate interplay between mapping and path planning, offering practical solutions that bridge theoretical optics and real-world robotic applications. Their research continues to influence the development of cost-effective, high-accuracy vision systems for autonomous vehicles and field robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
ROBOT VISION: CALIBRATION OF WIDE-ANGLE LENS CAMERAS USING COLLINEARITY CONDITION AND K-NEAREST NEIGHBOUR REGRESSION
4 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Alberta

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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