Application Case: VLA Pick-and-Carry¶
Scenario: a tabletop VLA tidying task with the Walker S2 EDU humanoid robot. The robot picks parts from the table, places them into a storage box, and then carries the box to a distant target.
Approach:
- Train a tabletop-tidying VLA model with the Thinker-IL-LAB toolchain.
- Deploy with the inference server and hot-load the picking model; call the service with the inference client.
- Build a task manager for robot navigation, carrying, and VLA picking to switch between multiple tasks and complete the full flow. For robot navigation and carrying, see the Walker S2 high-level motion interface.
Demo video¶
Further reading¶
- Real-robot workflow - End-to-end: real collection -> conversion -> training -> evaluation -> deployment
- Inference server - Warm start, ZMQ commands, model hot-swap