Richard Green
Papers
3
Total Citations
13
H-Index
2
About
Richard Green is a researcher whose work sits at the intersection of computer vision, robotics, and precision agriculture. His primary focus is on developing robust 3D imaging and sensing systems for autonomous platforms, particularly in challenging outdoor environments. A key contribution is his work on a hybrid computer vision and structured light system, which enables a robot to generate dense 3D reconstructions of crops while in motion. This system, detailed in his most-cited paper (8 citations), uses a line laser and subpixel localization to capture detailed plant geometry, a critical step for automated agricultural monitoring. He has also advanced the field of visual-inertial odometry (VIO), proposing a novel semi-synthetic approach for creating datasets that overcome the practical limitations of capturing high-accuracy ground truth outdoors. This work is vital for developing more robust navigation algorithms for field robots. Through his contributions to multi-camera system calibration and VIO dataset generation, Green is helping to build the foundational sensing capabilities needed for the next generation of autonomous agricultural and field robotics.
Research Focus
Key Achievements
Top Papers
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