Papers
4
Total Citations
135
H-Index
4
About
Matt Wildie is a leading researcher in field robotics, specializing in heterogeneous multi-robot systems, autonomous exploration, and perception for unstructured environments. His most impactful work centers on the DARPA Subterranean Challenge, where he was a key member of Team CSIRO Data61. Wildie’s major contributions include pioneering the integration of ground and aerial robots with unified perception and autonomy architectures, enabling robust exploration of dangerous, GPS-denied underground spaces. His highly cited 2022 paper (97 citations) details the team’s approach to balancing autonomy with human interaction, while a follow-up in 2024 (8 citations) describes how they tied for the top score in the competition. Beyond system-level integration, Wildie has made foundational contributions to understanding object detector failures, identifying five distinct “false negative mechanisms” in his 2022 work (22 citations). This research provides critical insights for improving reliability in safety-critical robotic perception. Wildie’s work directly advances the deployment of autonomous robots for search-and-rescue, mining, and infrastructure inspection, demonstrating real-world impact in extreme environments.
Research Focus
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