Estúdio de robótica nativo de IA

Projetar Treinar Implantar

  • Blocos de fluxo de trabalho visual
  • Assistente de IA integrado
  • Treino online e reprodução
O canvas visual do UnitPort. Nós de Robot, Sensors, Environment, Task, Trainer e Export ligados num único grafo de treino
Construa com IADiga o que quer. Ele constrói.
Canvas VisualArraste blocos. Não escreva código.
Treino e Simulação OnlineGPU na nuvem ou a sua própria máquina.

O treino de robôs nunca foi tão simples

How it works

From a robot model to a running policy

Four steps, one browser tab. You install something only when you want the training to run on your own machine.

  1. 01

    Bring a robot

    Start from one of the built-in robots, or import your own description and edit it in the browser.

  2. 02

    Compose the graph

    Six nodes carry the whole configuration — robot, observation, environment, task, checkpoint, trainer.

  3. 03

    Train

    On our cloud GPUs, on your own server, or on Isaac Lab on the machine under your desk.

  4. 04

    Check it, then take it

    Replay the trained policy in MuJoCo, then export a bundle with the contract a robot needs to run it.

AI Build

Diga à IA
Ela constrói a configuração

Aponte para a IA a correr no seu computador. Ou para qualquer endereço de API. Ou use apenas o nosso agente.

A sua IA local Qualquer endereço de API Ou o nosso agente
O painel AI Build. Um pedido em linguagem simples atualiza o nó Task
Visual Canvas

Blocos em vez de código

Tudo o que costumava escrever em código agora é um bloco. Arraste, conecte, pronto.

Sem código Arrastar e soltar Veja a configuração completa
Nós de Robô, Tarefa e Treinador conectados na tela do UnitPort
Editors

Bring your own robot, and your own ground to walk on

Two full editors, in the same tab as the canvas. Your files are read where you dropped them — a description you upload is parsed in your own browser, not on a server.

Robot Editor

Drop in a robot description with its meshes and it opens as an editable model, link by link and joint by joint.

  • URDF and MuJoCo XML are parsed in the browser; a USD stage is read by our service
  • Assign joint roles, check inertials, set the actuator model
  • Every value carries where it came from — yours, estimated, or a default we injected

Scene Editor

Author the terrain the policy learns on, with a brush and a set of generators — then use it in a training canvas.

  • Sculpt the ground, or generate stairs, slopes, boxes and rough terrain
  • Place props that really collide, and set where the robot spawns
  • Saved into your own library, ready for the environment node
Resource library

Import what you already have

Four kinds of asset, and more than one way in. Everything you import lands in your own storage, under your own account.

ModelsRobots, with their joints and inertials
FieldsTerrain and scenes to train on
MotionsReference clips for imitation
BundlesTrained policies, ready to deploy

From a public repository

Paste a GitHub link, pick the files, confirm. A robot description brings the meshes it names along with it.

From your own machine

Upload a file, or let the local helper copy a model, a scene, a clip or a finished run in from your own computer.

From the community

Subscribe to something another user published — it installs into your library ready to use.

Treinar e Implantar

Treine em qualquer lugar
Simule online

Conecte-se ao nosso GPU / seus servidores em nuvem ou sua própria máquina.

Nossa GPU na nuvem Seus próprios servidores Máquina local
Robô quadrúpede implantado a partir de um fluxo de trabalho do UnitPort

Da ideia ao robô treinado

Você controla cada custo. Comece completamente gratuito. Sem assinaturas mensais insistentes.