Papers
10
Total Citations
163
H-Index
5
About
Michael Magee’s pioneering research sits at the intersection of computer vision and autonomous robotics, with a career-long focus on enabling machines to perceive and navigate their environments. His most influential contribution, the 2005 paper on robot self-localization using a single calibration object (55 citations), introduced a groundbreaking procedure for uniquely determining a mobile robot’s 3D position by viewing a single sphere marked with calibration great circles—a method that simplified spatial reasoning for autonomous systems. Earlier foundational work, including his 1984 paper on robot guidance using computer vision (61 citations), established core principles for vision-based control. Magee also advanced monocular vision techniques for determining 3D position and orientation (1990, 12 citations) and developed optical target location methods for space robotics (1991, 8 citations), directly supporting autonomous control and teleoperation in orbital environments. His research on adaptive camera calibration (1990, 5 citations) addressed the critical challenge of maintaining accuracy in dynamic industrial settings where camera-to-target distances change. Through integrated planning frameworks that combined robot control with vision-based spatial reasoning, Magee demonstrated how autonomous systems could reason about and adapt to reconfigurable environments, laying essential groundwork for modern robotic perception and navigation.
Research Focus
Key Achievements
Top Papers
- 1Robot guidance using computer vision61 citations · 1984
- 2Determining the position of a robot using a single calibration object55 citations · 2005
- 3
- 4Optical target location using machine vision in space robotics tasks8 citations · 1991
- 5
- 6
- 7Adaptive camera calibration in an industrial robotic environment5 citations · 1990
- 8Task Panel Sensing with a Movable Camera4 citations · 1990
- 9A viewpoint independent modeling approach to object recognition4 citations · 1987
- 10