Papers
7
Total Citations
76
H-Index
4
About
Catharine McGhan is a leading researcher in human-robot collaboration, autonomous space robotics, and intent prediction, with a focus on enabling safe and efficient physical proximity between humans and machines. Her most influential work, "Human Intent Prediction Using Markov Decision Processes" (2015, 48 citations), introduced a novel modeling method that allows robots to anticipate a human’s task-level goals, improving decision-making in shared workspaces. This foundational contribution has shaped subsequent research in collaborative robotics. McGhan has also advanced risk-aware planning for autonomous planetary rovers, addressing the challenges of deep-space exploration where teleoperation is infeasible. Her work on "Human Productivity in a Workspace Shared with a Safe Robotic Manipulator" (2014, 7 citations) explores how humans and robots can efficiently complete independent tasks without explicit communication, enhancing both safety and productivity. Notably, she pioneered affordable virtual reality setups for aerospace robotics education (2019, 7 citations), making high-fidelity simulation accessible to students. Her early contributions to intent prediction for physically-proximal collaboration (2009) laid the groundwork for safer human-robot teams in future space missions. With a career spanning over a decade, McGhan’s research continues to influence autonomous systems, human-robot interaction, and aerospace engineering education.
Research Focus
Key Achievements
Top Papers
- 1Human Intent Prediction Using Markov Decision Processes48 citations · 2015
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- 3Human Productivity in a Workspace Shared with a Safe Robotic Manipulator7 citations · 2014
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