Shawn Hunt

Papers

Total Citations

H-Index

About

Shawn Hunt’s research focuses on advancing the autonomy and reliability of unmanned ground vehicles (UGVs), particularly in challenging, high-latency communication environments. His key contributions lie at the intersection of teleoperation, computer vision, and semi-autonomous control. In his most cited work, “Methods for UGV teleoperation with high latency communications” (8 citations), Hunt developed and demonstrated complementary control methods—including latency protection, predictive displays, and supervisory control—to mitigate the effects of communication delays that plague remote operations. He also pioneered terrain classification through sequential learning, addressing the complex visual variability of natural environments, and explored monocular visual ranging for checkpoint and security inspection robots. Hunt’s investigation into goal-based semi-autonomous algorithms, such as visual servoing and visual dead reckoning, provided critical evidence that these approaches can significantly improve remote operator performance. Though his citation counts are modest, his work represents foundational, practical steps toward making UGVs more capable in real-world, high-stakes scenarios where reliable communication is not guaranteed.