Edith Langer

Papers

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About

Edith Langer is a roboticist whose research focuses on enabling robots to understand and adapt to dynamic, open-world environments. Her key contributions lie in the areas of object change detection and autonomous semantic mapping, addressing the fundamental challenge of how robots can perceive not just static scenes, but the meaningful changes—new, moved, or missing objects—that define real-world spaces. Her most cited work, "Robust and Efficient Object Change Detection by Combining Global Semantic Information and Local Geometric Verification" (19 citations), pioneered a hybrid approach that fuses high-level semantic understanding with precise geometric checks to distinguish genuine object changes from simple scene rearrangements. This work directly addresses a critical gap in prior methods, which often confused novel objects with mere repositioning. Langer further advanced the field with her work on "On-the-fly detection of novel objects in indoor environments" (7 citations), which introduced efficient strategies for discovering new objects without exhaustive pre-mapping. Her recent research, "Where Does It Belong? Autonomous Object Mapping in Open-World Settings" (2 citations), tackles the complex problem of assigning semantic meaning to objects in ever-changing environments. Through her focused body of work, Langer is laying the groundwork for truly autonomous robots capable of tasks like tidying up, patrolling, and fetch-and-carry in unstructured human spaces.