Logan Schorr

Papers

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About

Logan Schorr’s research sits at the intersection of industrial robotics, computer vision, and accessible programming, with a focus on making automation smarter and more user-friendly. His most cited work introduces a novel method for robotic arm workspace detection that fuses 2D and 3D vision processing, enabling more reliable autonomy in dynamic environments—a critical step for real-world industrial adoption. This paper has already garnered 8 citations, signaling its growing influence. Schorr also contributed to the design of a high-temperature gripper for collaborative robots in additive manufacturing, addressing a key challenge in handling hot materials during 3D printing. In a different vein, his work on block-based programming for two-armed robots led to the development of Duplo, a visual programming environment that lowers the barrier to entry for complex multi-arm robot control. A comparative study of this system highlighted its potential to democratize industrial programming. Together, Schorr’s contributions advance both the hardware and software sides of robotics, making him a promising voice in the push toward more capable and approachable automation.