Papers
12
Total Citations
217
H-Index
6
About
John-David Yoder is a leading researcher in robotics and computer vision, with a focus on autonomous navigation, industrial automation, and sensor-based control. His most influential work centers on developing vision-guided systems for material handling and mobile robotics, notably through the creation of mobile camera-space manipulation (MCSM), a method that enables robotic forklifts to autonomously engage pallets using real-time visual feedback. His 2006 paper on this topic has garnered 75 citations, underscoring its impact on industrial robotics. Yoder has also made significant contributions to environment representation, pioneering a novel approach for computing occupancy grids directly from stereo-vision disparity space—a technique that enhances obstacle detection and road pixel analysis for intelligent vehicles. His 2012 paper on this method has 42 citations, and related works have collectively shaped probabilistic robotics for range sensing. Beyond research, Yoder has advanced robotics education, as seen in his 2020 paper on implementing multidisciplinary senior design sequences, reflecting his commitment to training future engineers. His work on teachless teach-repeat programming further demonstrates his drive to simplify industrial robot programming through vision-based automation, making him a key figure in bridging computer vision and practical robotics.
Research Focus
Key Achievements
Top Papers
- 1Automatic visual guidance of a forklift engaging a pallet75 citations · 2006
- 2
- 3Automatic Pallet Engagment by a Vision Guided Forklift34 citations · 2006
- 4Using the disparity space to compute occupancy grids from stereo-vision24 citations · 2010
- 5
- 6Teachless teach-repeat: Toward vision-based programming of industrial robots10 citations · 2012
- 7
- 8
- 9Control of Construction Robots using Camera-Space Manipulation3 citations · 1996
- 10EXTENDING TEACH–REPEAT TO NONHOLONOMIC ROBOTS3 citations · 1998