2026-04-07T06:50:06Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/65312025-04-29T13:54:10Zcom_20.500.11984_473col_20.500.11984_478

Digital Robot Judge: Building a Task-centric Performance Database of Real-World Manipulation With Electronic Task Boards Abu-Dakka, Fares J. So, Peter Sarabakha, Andriy Wu, Fan Culha, Utku Haddadin, Sami Task analysis benchmark Service robots robot sensing systems Automation Protocols Robotics aims to develop manipulation skills approaching human performance. However, skill complexity is often over- or underestimated based on individual experience, and the real-world performance gap is difficult or expensive to measure through in-person competitions. To bridge this gap, we propose a compact, Internet-connected, electronic task board to measure manipulation performance remotely; we call it the digital robot judge, or “DR.J.” By detecting key events on the board through performance circuitry, DR.J provides an alternative to transporting equipment to in-person competitions and serves as a portable test and data-generation system that captures and grades performances, making comparisons less expensive. Data collected are automatically published on a web dashboard (WD) that provides a living performance benchmark that can visualize improvements in real-world manipulation skills of robot platforms over time across the globe. 2024-06-17T07:12:06Z 2024-06-17T07:12:06Z 2024 http://purl.org/coar/resource_type/c_6501 1558-223X https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=174290 https://hdl.handle.net/20.500.11984/6531 eng Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ © 2024 IEEE IEEE