Trevor Henderson
Papers
2
Total Citations
18
H-Index
2
About
Trevor Henderson is a roboticist whose work lies at the intersection of autonomous exploration, information theory, and mapping. His primary research focuses on developing computationally efficient algorithms for information-theoretic mapping—a critical component for robots operating in unknown or hazardous environments, from disaster zones to outer space. Henderson’s key contribution is the FSMI (Fast Shannon Mutual Information) framework, which dramatically reduces the computational burden of evaluating mutual information for trajectory planning. While traditional methods struggle with real-time performance, FSMI enables robots to rapidly identify the most informative paths, balancing exploration and exploitation with unprecedented speed. His foundational paper on the topic has accumulated 14 citations, reflecting its growing influence in the field. Henderson’s work directly addresses a bottleneck in autonomous exploration, making it more practical for high-stakes applications like search and rescue and space exploration. By bridging the gap between theoretical information metrics and real-time robotic decision-making, he is helping to build the next generation of intelligent, self-directed robots capable of navigating the unknown.
Research Focus
Key Achievements
Top Papers
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