Dylan Covell

West Virginia University, Morgantown High School

Papers

Total Citations

H-Index

About

Dylan Covell is a robotics researcher whose work focuses on autonomous systems for extreme environments and innovative approaches to robot design. His most impactful contribution is the development of "Rhino," an autonomous robot designed for mapping underground mine environments. This work, published in 2023 with 18 citations, addresses critical safety challenges in mining by enabling robotic inspections of unstable pillars and roofs, thereby reducing the risk of accidents from collapses. Covell’s research demonstrates a practical application of robotics to enhance worker safety and operational efficiency in hazardous settings. Beyond applied robotics, Covell has explored the theoretical underpinnings of engineering design. His 2022 thesis, "Top-Down & Bottom-Up Approaches to Robot Design," examines various design methodologies, blending them to create an accessible project design flow that incorporates bottom-up principles. This work highlights his interest in how robots are conceptualized and built from the ground up, offering insights for both students and practitioners in the field. With a growing citation record, Covell is establishing himself as a researcher who bridges practical field robotics with foundational design theory, making his work relevant to those interested in autonomous systems, safety engineering, and robot design methodologies.