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About

David C. Conner is a robotics researcher whose work spans autonomous navigation, hybrid control systems, humanoid robotics, and industrial automation. His most influential contribution lies in developing compositional frameworks for robot navigation and control — designing local feedback control policies that combine to solve global navigation problems in constrained environments. His 2004 paper on composing local potential functions (148 citations) laid foundational groundwork in this area, with subsequent papers on hybrid controller synthesis and flow-through policies extending these ideas to fully actuated and nonholonomic systems. Conner also made significant practical contributions to the automotive industry, developing trajectory planning tools for paint deposition on geometrically complex surfaces (101 citations), with follow-on work on hierarchical surface segmentation for uniform coverage. His research took a high-profile turn with Team ViGIR's participation in the 2013 DARPA Robotics Challenge (81 citations), where he helped advance human-robot teaming strategies for disaster response using humanoid platforms. Additional work on formal specification-based control — demonstrated through autonomous valet parking scenarios — showcases his ability to bridge rigorous theoretical guarantees with real-world robotic deployment. With over 650 total citations, Conner's research meaningfully connects control theory, planning, and applied robotics.