JDO / EMBODIED INTELLIGENCE TECHNOLOGY

Embodied AI Technology for Vehicles and Robots

The JDO AI system connects perception, decision-making, execution and feedback, adapting to tasks in vehicles and robots.

Explore the AI System

JDO AI System

Support vehicle-wide coordinated control by combining in-cabin, external, and vehicle-state inputs.

Cognitive System · Understanding & Decision-Making

Use terrain, road-surface variation and vehicle state to understand context and task goals and coordinate vehicle-wide systems.

Execution System · Execution & Feedback

The brain coordinates the task. The cerebellum executes in real time across intelligent-driving, chassis and cockpit domains, then feeds status back to the brain.

Driving: Driving strategy
Chassis: Suspension and attitude
Cockpit: Interaction and prompts

A light gray-and-white 3D public space with pedestrians near a building entrance and a white vehicle on the road

One System, Multiple Platforms

A shared foundation for vehicles and robots, adapted to each platform

Layered Memory

Tasks, Experience & Long-Term Preferences

Adaptive Reasoning

Adjust reasoning depth to the task

Scenario Prediction

Anticipate what may happen next

Automotive Technology Experience

Provide the perception, understanding, and memory foundation for in-cabin interactions and tasks.

Vision-Language Understanding (VLM)

Connect vision and language to understand road conditions outside the cabin, objects, interfaces, and questions.

In-Vehicle Voice and On-Device Response

In-car voice focuses on understanding user needs amid cabin noise; on-device responses are designed with weak or no connectivity in mind.

State and Health-Related Sensing

When authorized and supported by available data, assist with assessments and reminders without replacing medical diagnosis.

Driver and Occupant Monitoring

Provide inputs on driver and passenger state, including child-related cues, to support reminders, interactions, and services.

Multimodal Fusion and Context Understanding

Connect vision, speech, language, and vehicle-state signals to form usable context.

Memory

Within the scope authorized by the user, retain preferences and task context so services can continue seamlessly.

Technology Stack Support

JDO Canghai AI Core

Multimodal Models & Perception Algorithms

Connect users' words with visual context.

A passenger, an illuminated display, and a city outside the windows of a light gray-and-white 3D cockpit

Natural Language

Natural language models help interpret what people in the vehicle say and need.

Vision-Language & Perception

Combine vision-language and perception algorithms to support image understanding and object recognition.

AIOS

Context Management & Agent Runtime

Use the runtime framework to adapt to different platforms.

Model inference efficiency is optimized for on-device deployment, taking chip computing capacity and operating conditions into account.

A physical illuminated display showing map, media, and environment widgets inside a light gray-and-white 3D cockpit

Runtime & Context

Manage task context and history, and orchestrate Agents.

Platform Integration & Adaptation

Use APIs, containers, and middleware to integrate the required models and capabilities.

Generative Components & Themes

Explore component generation, theme changes, and interface composition.

AI Agent

Intent Parsing, Task Planning & Tool Invocation

Contextual information and task objectives guide multiple agents as they work together to complete tasks in mobility services and robotics operations.