T. Celinski
Papers
1
Total Citations
5
H-Index
1
About
T. Celinski is a researcher whose work lies at the intersection of robotics, sensor fusion, and perceptual quality control. His most-cited paper, "Improving sensory perception through predictive correction of monitoring errors" (2003, 5 citations), introduces a novel approach to managing perception in multi-sensor robotic systems. By employing a weighted least squares algorithm to predict and correct monitoring errors from low-performance sensors, Celinski enables systems to dynamically decide when to engage high-performance monitors, balancing cost and accuracy. This contribution addresses a fundamental challenge in autonomous systems: maintaining reliable perception while optimizing computational and energy resources. Though his citation count is modest, the work demonstrates a practical, algorithmic solution to a persistent problem in robotics—predictive error correction for sensor management. Celinski’s research is particularly relevant for students and engineers working on resource-constrained robotic platforms, where efficient sensory processing is critical. His approach offers a clear framework for improving perception without over-reliance on expensive hardware, making it a valuable reference in the fields of intelligent control and adaptive sensing.
Research Focus
Key Achievements
Top Papers
- 1