LET: Full-Size Humanoid Robot Real-World Multi-Task Data

LET Dataset is a collection of real-world multi-task data from the Kuavo 4 Pro full-size humanoid robot, covering multiple scenarios and operation types. It was created by LejuRobotics and last updated on March 13, -2026. The dataset is designed to support scalable robot learning in real environments.

Use Cases

• Training robot manipulation models based on real-world multi-task data.
• Developing mobility control algorithms based on data from multiple scenarios.
• Improving human-robot interaction systems based on real-world operation types.
• Benchmarking scalable robot learning methods in real environments.

Strengths

• Data is collected from a full-size humanoid robot (Kuavo 4 Pro) in real-world environments.
• Covers multiple scenarios and operation types for multi-task learning.
• Last updated on March 13, -2026.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and dataset size are unknown, which may limit suitability assessment.
• License information is unknown, which may restrict usage.

Provenance

Source

LejuRobotics

Collection Method

Collected based on the full-size humanoid robot Kuavo 4 Pro.

Time Range

Unknown

Freshness

Last updated 2026-03-13 08:17:11; freshness should be verified.

Geography

Unknown