The World Humanoid Robot Games (世界人形机器人运动会) released over 2,500 hours of real-world operations for embodied-AI training and validation.

The second World Humanoid Robot Games (世界人形机器人运动会) released what was described as the first complete dataset from a world-level humanoid-robot competition. The dataset contains more than 2,500 hours of real-world operational data gathered by multiple institutions during training, preparation and formal competition.

The organizers said the dataset can directly support embodied-AI model training and research. It is also intended to provide universities and research institutions with data for algorithm training and scenario validation.

Across the five-day event, more than 100 robot models and over 2,000 humanoid robots competed. Thousands of operating hours and more than 10,000 motion-capture instances were recorded.

Reported competition results included a sub-10-second 100-meter run and a 3.4-meter standing high jump. The 400-meter record improved from 1 minute 28.03 seconds at the previous event to 45.66 seconds for the small-robot group and 38.15 seconds for the large-robot group, while the 1,500-meter record improved from 6 minutes 34.40 seconds to 2 minutes 21.64 seconds.