Papers
16
Total Citations
183
H-Index
8
About
Jonathan Black’s research career bridges two transformative eras in robotics and aerospace: the precision engineering of industrial manipulators and the intelligent autonomy of small satellites and drones. His early work pioneered the use of Taguchi methods to quantify and optimize robot process capability—accuracy, repeatability, and stability—providing a low-cost, systematic framework that remains foundational for manufacturers seeking to maximize robotic performance. These contributions, alongside his comprehensive review of robot metrology (41 citations), established him as a key voice in manufacturing automation. In the 2010s, Black shifted his focus to onboard image processing and autonomous flight systems, addressing the critical lag in space-grade computing. His work on optical flow background subtraction for PTZ cameras and a distributed multipurpose UAV system using 3D position tracking and ROS (14 citations) directly enabled real-time computer vision in constrained environments. Most recently, his SpaceDrones 2.0 project (2022) creates hardware-in-the-loop simulations for orbital and deep-space machine learning, using free-flying drone platforms to validate AI tasking before launch. With over 160 total citations across four decades, Black’s research uniquely connects industrial robotics’ rigorous metrology with the emerging demands of autonomous space exploration.
Research Focus
Key Achievements
Top Papers
- 1A review of recent developments in robot metrology41 citations · 1988
- 2Onboard Image Processing for Small Satellites35 citations · 2018
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- 6Optical flow background subtraction for real-time PTZ camera object tracking14 citations · 2013
- 7Determining robot process capability using Taguchi methods10 citations · 1989
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- 10Control of an industrial robot subjected to base mobility4 citations · 1994