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About

Dylan Hendrickson is a theoretical computer scientist whose research sits at the intersection of computational complexity, motion planning, and robotics. His most significant contributions center on developing a rigorous mathematical framework for understanding *why* certain problems in motion planning and puzzle-solving are computationally hard. Hendrickson's landmark work on "gadget theory" — appearing in multiple iterations between 2018 and 2020 and accumulating citations across versions — establishes a general complexity theory for robot motion planning through networks of state-based gadgets. By characterizing which gadget types lead to NP-hardness or PSPACE-completeness, his framework provides researchers with powerful tools to classify the difficulty of video game mechanics, puzzles, and robotic navigation problems in a unified way. Beyond motion planning complexity, Hendrickson has contributed to modular robotics, co-authoring work on reconfiguring pivoting robots in hexagonal grids — deriving both efficient algorithms and hardness results for reaching target configurations. Though early in his career with modest citation counts reflecting the specialized nature of theoretical CS research, his work addresses foundational questions that underpin algorithm design for autonomous systems and combinatorial game theory, making it a valuable resource for students studying computational complexity and robotics.