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#Annotation and QA

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2026-09-29Tue
  1. Haozhi Qi33

    **Summary:** The OSMO tactile glove, an open-source tool for human-to-robot skill transfer, is now available as a DIY kit. It captures 3-axis tactile signals from human demonstrations and enables the same sensing hardware to be used on robot hands. The project, led by Jessica Yin and supported by several researchers, provides publicly accessible hardware designs, firmware, and assembly instructions. The kit is not for profit, with the goal of supporting reproducibility and advancing tactile research. The DIY kit is available at [link], and the project page is at [link].

  2. RoboSpeak — WeChat83

    Built Over 100 Data Training Sites, Why Are Robots Still 'Hungry'?

    The article explores the issue of data scarcity in the field of embodied intelligence, pointing out that although there are already a large number of data collection centers, high-quality and reusable data remains severely insufficient. The article analyzes structural contradictions such as high data collection costs, inconsistent quality, fragmented formats, and lack of cross-ontology reusability. It introduces Wu Wen Tech's solution of building a data foundation through a Real2Sim2Real closed-loop system, including large-scale data collection, automated annotation, and simulation training technologies, ultimately forming a data-driven flywheel to promote the development of embodied intelligence.

    Editorial context：The article highlights the critical data scarcity in embodied AI, emphasizing the gap between the scale of robot models and the availability of high-quality physical interaction data. It identifies structural issues such as high collection costs, quality inconsistencies, and lack of standardization as major barriers. The solution proposed by Wu Wen Tech involves a Real2Sim2Real closed-loop system,

2026-09-15Tue
2026-09-07Mon
  1. IEEE Spectrum — Robotics88

    This Robot Will Draw Your Blood Now

    Aletta, the first autonomous blood-draw device approved for use in the U.S., uses imaging and robotics to perform blood draws with high success rates, even in challenging cases. While it addresses staffing shortages in clinical labs, concerns about skin tone bias and sample quality persist, requiring further validation.

    Editorial context：Aletta, the first autonomous blood-draw device authorized in the U.S., combines imaging and robotics to perform blood draws with high success rates, though concerns about skin tone bias and sample quality remain. The device addresses staffing shortages in clinical labs but requires further validation to ensure equitable performance across all demographics.