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Interactive Robotics Laboratory
Yu Gu, Professor
College of Engineering and Mineral Resources
WVU Home

Heath Cottrill

Cottrill Portrait


Mechanical Engineering

EDUCATION

    BS Aerospace Engineering, West Virginia University (2022)

    BS Mechanical Engineering, West Virginia University (2022)

    MS Mechanical Engineering, West Virginia University (Est. 2024)

DIGITAL FOOTPRINT

LinkedIn

BIO

As a proud native of the state, Heath had a lifelong dream of furthering his education at West Virginia University. In 2018, that dream transformed into a vivid reality when he was honored with the Foundation Scholarship, the highest academic distinction bestowed by the University. Empowered by this prestigious opportunity, he earned his Bachelor of Science degrees in both Mechanical and Aerospace engineering. Throughout this academic journey, Heath unearthed his profound passion for robotics, nurtured both within the confines of his coursework and through his involvement with the University Rover Challenge (URC) team. Consequently, he recently made the resolute choice to extend his educational voyage by pursuing a Master of Science degree in mechanical engineering, all while remaining rooted at WVU. Today, Heath’s work is sponsored by the West Virginia Space Grant Consortium (WVSGC) where he focuses on sensor fusion technologies.

RESEARCH STATEMENT

In the quest for exploration missions in space, robotic systems play an indispensable role in environments where human presence is unfeasible. The cornerstone of these robots' effectiveness lies in precise localization, achieved through the integration of internal (proprioceptive) and external (exteroceptive) data sources. While internal sensors can introduce drift over time, real-time updates from external sources mitigate this issue. Unlike Earth, extraterrestrial planets lack the infrastructure of GNSS. My research is dedicated to enhancing robotic localization in challenging environments, with a current focus on Venusian missions. I employ map matching techniques that harness scalar fields to align sensor data with predefined maps, effectively minimizing error growth. This work aims to empower robots to navigate and operate efficiently in demanding extraterrestrial conditions, thus advancing our understanding of the solar system and beyond.

KEYWORDS

  • Sensor Fusion
  • Localization
  • Path Planning