Theia Henderson

IIT@MIT, Massachusetts Institute of Technology

Papers

Total Citations

H-Index

About

Theia Henderson is a robotics researcher whose work centers on information-theoretic exploration, autonomous navigation, and efficient decision-making under uncertainty. Her major contributions lie in developing computationally tractable methods for robots to explore unknown environments—critical for applications like search and rescue and space exploration. Henderson’s most cited paper, “FSMI: Fast computation of Shannon mutual information for information-theoretic mapping” (2020, 35 citations), introduces a rapid algorithm for calculating mutual information, enabling real-time trajectory planning without sacrificing accuracy. Building on this, her follow-up work, “An Efficient and Continuous Approach to Information-Theoretic Exploration” (2020, 16 citations), proposes a continuous optimization framework that reduces computational overhead, making advanced exploration feasible on resource-constrained platforms like drones and rovers. Together, these papers have garnered over 50 citations, reflecting their impact on bridging theory and practice in autonomous exploration. Henderson’s achievements include advancing the state of the art in information-theoretic mapping, offering practical solutions that extend robotic autonomy to real-world, time-critical missions. Her work is a cornerstone for students and researchers seeking to push the boundaries of efficient, intelligent exploration in robotics.