VLA and imitation learning developmentTeach the motion you cannot write out, from a human demonstration.

Factory/warehouse transportation simulation

Unitree G1

In an Isaac Sim physics simulation, G1 held a 0.25 kg box with both hands, walked approximately 1.2 m, and placed it on another table. This is simulated footage.

RealMan RMC-AIDAL

We grasped the handle of a hypothetical transport case with a body size of 30 x 20 x 20 cm and a total weight of 10 kg, and verified the process of transporting it on wheels for approximately 1.2 m, placing it on a stand, and then releasing it. This is a physical simulation that corrects the center of gravity and contact settings of the public CAD model, and does not guarantee the load capacity of the robot.

RealMan RMC-AIDAL: 10 kg case transport with both arms

We verified the operation of holding a hypothetical transport case with a body size of 30 x 40 x 20 cm and a total weight of 10 kg with both hands using the left and right handles, transporting it approximately 1.2 m, and placing it on a stand. During transportation, contact between the left and right hands and load sharing are recorded. This is a physical simulation that corrects the center of gravity and contact settings of the public CAD model, and does not guarantee the load capacity of the robot.

You can also consult with us about simulations and demonstration experiments tailored to your business, such as replenishing shelves, supplying parts boxes, and sorting.

Environment/box 3D materials: NVIDIA SimReady / codepawl/simready-glb · CC BY 4.0 · Assets were converted, resized, and assigned adjusted surface materials.

Some work cannot be written as a program

If it is grasping a fixed object at a fixed position, writing the motion out is surer and faster. Bringing learning into it only makes sense for work you cannot write out.

Objects that differ one from another, that are placed differently each time, that deform like a bag or cloth. You cannot write out every branch for work like that, and teaching the motion from a human demonstration becomes the realistic approach.

Learning is not a cure-all, though. How much data is needed changes with the difficulty of the task and the success rate you require, and part of it cannot be read until you start collecting. We run a trial collection first and move to the full one once we can judge.

Implementation Case: Gemini 4 Argon × Unitree G1 (Turning Vision into Action)

Unitree G1 picked up a plastic bottle using Gemini 4 Argon—with no hard-coded motions, just AI turning camera vision directly into action. Even when the bottle is repositioned, the AI perceives the scene and generates grasping motions on the fly.

We design and implement vision-to-action generation using foundation models and VLAs, alongside imitation learning from human demonstrations, tailored to your target robot and site conditions.

What we can take on

Data is the foundation of all of it

Whether learning works is decided by the data before the model. Too few viewpoints, no failure cases, task conditions that drift — train on data like that and it will not run on site.

We design the target task, the machine, the volume and the quality criteria, then take the data from the real robot. There is also a setup that records vision, action, dialogue and non-verbal signals in sync while the robot works under remote operation.

We can also take on the data collection alone, or advise only on building the collection environment.

NVIDIA GEAR Sonic × Unitree G1: Real robot demonstration

We ran NVIDIA GEAR Sonic on a Unitree G1 robot and verified its operation. Watch the video to see the demonstration.

Gemini 4 Argon × Unitree G1: Turning Vision into Action

Unitree G1 just picked up a plastic bottle using Gemini 4 Argon. No hard-coded motions. Just AI turning vision into action. The future of robotics is getting real.

Even when the bottle is moved and placed again, the AI visually understands the scene and generates the grasping motion. We provide Physical AI and VLA implementation on the Unitree G1 as well as custom PoC and verification development tailored to your operations.