Jeffrey Schoonover

Papers

Total Citations

H-Index

About

Jeffrey Schoonover is a robotics researcher focused on advancing the precision and productivity of industrial automation. His primary research areas include high-speed spatial curve tracking, motion primitives, and coordinated control for dual-arm robotic systems. Schoonover’s major contributions lie in developing algorithms that reconcile the often conflicting demands of tracking accuracy, path speed, and motion uniformity in manufacturing processes such as spraying, welding, and additive manufacturing. His 2023 paper on high-speed, high-accuracy spatial curve tracking using motion primitives (11 citations) provides a foundational framework for improving single-robot performance. Building on this, his 2024 work on fast and accurate relative motion tracking for dual industrial robots (6 citations) addresses a critical bottleneck in process throughput by enabling coordinated dual-arm setups to overcome the speed limitations of single robots. These contributions are directly relevant to industries seeking to enhance productivity without sacrificing precision. Schoonover’s research is notable for its practical, application-driven approach, offering tangible solutions for real-world manufacturing challenges.