Robonix

Robonix — An Agentic Operating System for Embodied AI

A system substrate for building embodied intelligence across heterogeneous robots.

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Robonix is a general-purpose agentic operating system designed for embodied artificial intelligence. It employs large language models (LLMs) and vision-language models (VLMs) to convert natural-language tasks into Robot Task Description Language (RTDL) programs, which are then executed to complete the specified tasks. The primary advantages of Robonix include the following:

• (1) Hardware–software decoupling. Robonix utilizes layered capability abstractions (Task, Skill, Service, Primitive) to separate software functionality from robot-specific hardware. These abstractions establish standard interface definition language (IDL) interfaces, enabling the reuse of compatible primitives, services, and skills across different robotic platforms.
• (2) Adaptability to diverse user tasks, robot capabilities, and environments. Robonix leverages LLMs and VLMs to generate RTDL programs tailored to each user's task, the robot's capabilities, registered skills, environmental conditions, and body state. This approach enables Robonix to accommodate a wide range of natural language tasks, robotic hardware, and operational environments.
• (3) Observable and verifiable execution. Robonix explicitly represents the model's program in RTDL, allowing for inspection of its structure. The system performs program validation prior to execution and can verify specified outcomes upon completion.

Design of Robonix

Figure 1. The architecture of Robonix.

Figure 1 illustrates the overall architecture of Robonix. The user interacts with Liaison, which verifies the user with Keystone. Liaison delegates the task to Pilot. The model orchestrates skills and services for the task by writing an RTDL program; Pilot checks it and forwards it to Executor. Sentinel monitors Executor, while Scene keeps the semantic map (objects and their relations) and the spatial map of the outer world. Custom services sit beside Scene: navigation, SLAM mapping, object detection, grasp-pose estimation, motion planning, memory, and more from the package catalog. Atlas, Nexus, Chronos, Scribe, and Vitals provide the capability catalog, messaging, time, logging, and health that the rest build on. At the bottom, Soma is the body abstraction. A URDF gives the body's geometry and coordinate frames; a YAML body description gives its component tree (base, arm, gripper, camera) and the primitive capabilities each component provides. On the right, the skill library holds skills such as picking, handing over an item, pouring, and folding, often vision-language-action (VLA) models; skills can be learned in a simulator such as Webots, MuJoCo, or Isaac Sim and then deployed to real robots through Robonix. Where it meets Soma sit the preset skills the vendor ships with the body, such as a dance or a backflip.