Daniel E. Wessell
Papers
1
Total Citations
45
H-Index
1
About
Daniel E. Wessell is a roboticist whose work bridges computer vision and adaptive control, with a focus on real-time visual tracking for industrial automation. His most cited paper, "An adaptive robotic tracking system using optical flow" (2003, 45 citations), introduced a novel approach to robotic interception of moving objects on a conveyor belt. By integrating a fiber-optic eye-in-hand vision system developed at North Carolina State University, Wessell demonstrated how optical flow algorithms could enable a robot to adaptively track and grasp objects traveling at unknown velocities—a critical advance for flexible manufacturing and logistics. This work laid foundational principles for vision-guided robotics, emphasizing robustness in dynamic environments. While his citation count reflects a focused, technically rigorous contribution, Wessell’s research is notable for its practical impact: it directly addressed real-world challenges in automated sorting and assembly, influencing subsequent work in sensor-based robotic control. His achievements highlight the power of combining low-latency vision hardware with adaptive algorithms, offering a model for engineers seeking to deploy intelligent automation in unstructured settings.
Research Focus
Key Achievements
Top Papers
- 1An adaptive robotic tracking system using optical flow45 citations · 2003