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

Abu-Dakka, Fares J. 2024-06-17T07:12:06Z 2024-06-17T07:12:06Z 2024 1558-223X https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=174290 https://hdl.handle.net/20.500.11984/6531 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. eng Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ © 2024 IEEE Task analysis benchmark Service robots robot sensing systems Automation Protocols Digital Robot Judge: Building a Task-centric Performance Database of Real-World Manipulation With Electronic Task Boards http://purl.org/coar/resource_type/c_6501