AGIBOT Introduces Worken to Measure Productive Robot Work at AGIBOT Innovation Day 2026
AGIBOT introduces Worken to measure productive robot work at AGIBOT Innovation Day 2026
AGIBOT unveiled Worken, a framework to measure productive robot work in real-world environments, alongside new hardware and AI models. The framework combines active robot count, autonomous working hours, and output efficiency ratio to assess robotic productivity. The company also launched AHA3 hardware platform and GO-3 Preview model, emphasizing deployment-first innovation.
AGIBOT launches named hardware and platform components and proposes a task-normalized productivity framework. Useful integration and purchasing developments; Worken is an unvalidated proposal, ecosystem counts do not prove adoption, and planned open source is not current access.
Source: Robotics & Automation News · Read original article ↗
Loading article text…
What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- paper: not_reported
- code: not_reported
- weights: not_reported
- dataset: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
ork Hours,” bringing three factors into a proposed measurement framework: Worken = Number of Active Robots × Autonomous Working Hours × Output Efficiency Ratio The first factor counts robots actively performing tasks in real-world environments, rather than units simply manufactured or held in inventory. The second measures time spent working autonomously, rather than total powered-on time. The third assesses producti
Open source S9
ilities through both structured training and experience gained from real-world operations. AGIBOT also highlighted GO-3 Preview’s benchmark performance. According to evaluation results presented at the event, the model ranked first in both task success rate and process score on RoboDojo, achieved the highest overall score on RoboTwin, and ranked first in overall score on RoboColiseum. These results demonstrate the mo
Open source S19
del’s performance across multiple evaluation frameworks covering robotic manipulation and task execution. Across task and interaction intelligence, AGIBOT is seeking to connect data, models, robot hardware and operating scenarios across pre-training, post-training, deployment and day-to-day operations. Feedback from real tasks can then inform subsequent improvements to models and workflows, creating a deployment-driv
Open source S20
Source：Robotics & Automation News · roboticsandautomationnews.com