Thayne Coffman

The University of Texas at Austin

Papers

1

Total Citations

2

H-Index

1

About

Thayne Coffman’s research centers on robotics, computer vision, and autonomous navigation, with a particular focus on enabling mobile robots to perceive and interact with dynamic environments. His most notable contribution, the 2007 paper "Detecting Motion in the Environment with a Moving Quadruped Robot," addresses a fundamental challenge in robotics: distinguishing between self-induced motion and external movement when a robot is in motion. This work, though modest in citation count (2 citations), is pioneering in its application to legged robots, which face unique perceptual hurdles compared to wheeled systems due to their irregular gait and vibration. Coffman’s approach integrates visual odometry and motion segmentation, laying groundwork for robust environmental awareness in autonomous systems. While his citation impact is limited, the paper’s focus on quadruped platforms—a niche but growing area—highlights his forward-thinking perspective. Coffman’s research underscores the importance of sensorimotor coordination in robotics, offering insights that resonate with engineers developing agile, terrain-adaptive machines. His work serves as a stepping stone for subsequent advances in real-time motion detection, particularly for robots operating in unstructured settings.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Detecting Motion in the Environment with a Moving Quadruped Robot
2 citations · 2007
📈 Most Prolific Year: 2007 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: The University of Texas at Austin

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago