LimX Dynamics Releases LimX VGM Embodied Robot Operation Algorithm

Recently, LimX Dynamics released a video generation-based embodied operation algorithm (VideoGenMotion) called LimX VGM, marking the first domestic application of human operation data directly to robot operations.

Founded in 2019, LimX Dynamics is an embodied intelligence robotics company focused on developing full-size general-purpose humanoid robots and innovative products like biped robots.

LimX Dynamics is committed to disruptive innovation in embodied intelligence, unlocking AGI's generalization capability in the physical world. With self-developed core hardware and software technologies, coupled with leading humanoid base models, it aims to create universal mobile operation platforms and embodied intelligence software tools to serve innovators and integrators, promoting broad applications in fields like research, manufacturing, business, and home.

Embodied intelligence has always faced significant data challenges: human operation videos cannot be directly applied to robot operations. While large models can generate behavior trajectories and operational data from these videos, they often lack precision, deviate from physical laws, and contain flaws such as hallucinations. Even with accurate data, it's still not directly applicable to robot operations.

LimX VGM addresses this by retraining existing video generation models with human operation video data, requiring only scene images and task instructions as prompts. This allows for task understanding, object manipulation trajectory generation, and robot execution in a zero real-machine sample data process, with multi-platform generalization.

The LimX VGM workflow includes three key steps:

1. Training Phase: Collect real human operation videos and retrain existing video generation models.

2. Inference Phase: Using initial scenes and task instructions as prompts, the retrained model generates human operation videos with depth information, which are then used to create robot behavior for operations.

3. Execution Phase: The algorithm outputs behavior calculations that align with robot operation logic, leading to corresponding operation trajectory execution.

LimX VGM does not create video generation models but leverages existing frameworks and their vast knowledge and intelligence. Since video generation models compress historical data (including videos, images, text, etc.), they contain vast human operation data. Through effective training, LimX VGM can extract critical information useful for operation tasks and convert it into robot operation strategies and behaviors.

With this capability, LimX VGM only requires minimal human operation video data for robot operations, eliminating the need for real machine data collection, making data gathering simpler, cost-effective, and efficient. As the "knowledge base" of large models continues to upgrade, LimX VGM will have richer, more comprehensive operational knowledge, generating more effective operational strategies and further enhancing the algorithm's generalization.

LimX VGM marks a new beginning and a key step in LimX Dynamics' exploration of embodied operation. The company will continue to optimize LimX VGM's capabilities, drive algorithm adaptation for advanced video generation models like Cosmos, improve inference efficiency, and gradually achieve real-time video generation. Additionally, it will further optimize the performance of spatial intelligence modules, improving the precision of operation execution.