Release Notes#

Click each tab to learn about the new and updated features in each release of Embodied Intelligence SDK.

Embodied Intelligence SDK v25.36 enhances model optimization capabilities with OpenVINO™ toolkit and provides typical workflows and examples, including Diffusion Policy (DP), Robotic Diffusion Transformer (RDT), Improved 3D Diffusion Policy (IDP3), Visual Servoing (CNS) and LLM Robotic Demo. This release has also updated the real-time optimized best-known configuration (BKC) on improving AI and control performance, and supporting the Intel® Arc™ B-series graphics card (B570).

New Features:

  • Updated real-time optimization BKC, including BIOS and runtime optimization, balancing performance with AI and control consolidation.

  • Added support for Intel® Arc™ B-series (Battlemage) graphics card (B570).

  • Fixed deadlock issue when reading i915 perf event in Preempt-RT kernel.

  • New EtherCAT Master stack features supporting user-space EtherCAT Master and multiple EtherCAT masters.

  • Added Diffusion Policy pipeline with OpenVINO™ toolkit optimization.

  • Added Robotics Diffusion Transformer (RDT) pipeline with OpenVINO toolkit optimization.

  • Added Improved 3D Diffusion Policy (IDP3) model with OpenVINO toolkit optimization.

  • Added Visual Servoing (CNS) model with OpenVINO toolkit optimization.

  • Provided new tutorials for typical AI model optimization with OpenVINO toolkit.

  • ACRN hypervisor’s initial enablement on Arrow Lake platform.

  • Added new Dockerfile to build containerized Robotics Development Toolkit (RDT) pipeline.

Known Issues and Limitations

  • ACRN hypervisor feature and performance

    #. iGPU performance degradation observed when using passthrough iGPU to VM on ACRN hypervisor.

    #. Display becomes unresponsive in VMs when running concurrent AI workloads with iGPU SR-IOV enabled on ACRN hypervisor.

The following model algorithms were added and optimized by OpenVINO™ toolkit:

Algorithm

Description

Qwen2.5VL

Qwen2.5VL model_tutorials

Whisper

Whisper model_tutorials

FunASR (Automatic speech recognition)

Refer to the FunASR Setup funasr-setup in LLM Robotics sample pipeline

Visual Servoing - CNS model_cns

A graph neural network-based solution for image servo utilizing explicit keypoints correspondence obtained from any detector-based feature matching methods

Diffusion Policy model_dp

A visuomotor policy learning model in the field of robotic visuomotor policy learning, which represents policies as conditional denoising diffusion processes

Improved 3D Diffusion Policy (iDP3) model_idp3

A diffusion policy model enhancing capabilities for 3D robotic manipulation tasks

Robotic Diffusion Transformer (RDT-1B) model_rdt

A diffusion-based foundation model for robotic manipulation

The following pipelines were added:

Pipeline Name

Description

Diffusion Policy diffusion_policy

An innovative method for generating robot actions by conceptualizing visuomotor policy learning as a conditional denoising diffusion process

Robotics Diffusion Transformer (RDT) robotics_diffusion_transformer

A RDT pipeline provided for evaluating the VLA model on the simulation task

LLM Robotics Demo llm_robotics_demo

A code generation demo for robotics, interacting with a chatbot utilizing AI technologies such as large language models (Phi-4) and computer vision (SAM, CLIP)

Embodied Intelligence SDK v25.15 provides necessary software framework, libraries, tools, BKC, tutorials and example codes to facilitate embodied intelligence solution development on Intel® Core™ Ultra Series 2 processors (Arrow Lake-H), It provides Intel Linux LTS kernel v6.12.8 with Preempt-RT, and supports for Canonical Ubuntu OS 22.04, introduces initial support for ROS2 Humble software libraries and tools. It supports many models optimization with OpenVINO™ toolkit, and provides typical workflows and examples including ACT manipulation, ORB-SLAM3, etc.

New Features:

  • Provided Linux OS 6.12.8 BSP with Preempt-RT

  • Provided Real-time optimization BKC

  • Optimized IgH EtherCAT master with Linux kernel v6.12

  • Added ACT manipulation pipeline with OpenVINO™ and Intel® Extension for PyTorch framework optimization

  • Added ORB-SLAM3 pipeline focuses on real-time simultaneous localization and mapping

  • Provided typical AI models optimization tutorials with OpenVINO™ toolkit

Known Issues and Limitations

  • There is a known deadlock risk and limitation to use intel_gpu_top to read i915 perf event in Preempt-RT kernel, it will be fixed with next release.

The following model algorithms were optimized by OpenVINO™ toolkit:

Algorithm

Description

YOLOv8 model_tutorials

CNN-based object detection

YOLOv12 model_tutorials

CNN-based object detection

MobileNetV2 model_tutorials

CNN-based object detection

SAM model_tutorials

Transformer-based segmentation

SAM2 model_tutorials

Extend SAM to video segmentation and object tracking with cross attention to memory

FastSAM model_tutorials

Lightweight substitute to SAM

MobileSAM model_tutorials

Lightweight substitute to SAM (Same model architecture with SAM. See OpenVINO toolkit’s SAM tutorials for model export and application)

U-NET model_tutorials

CNN-based segmentation and diffusion model

DETR model_tutorials

Transformer-based object detection

DETR GroundingDino model_tutorials

Transformer-based object detection

CLIP model_tutorials

Transformer-based image classification

Action Chunking with Transformers - ACT model_act

An end-to-end imitation learning model designed for fine manipulation tasks in robotics

Feature Extraction Model: SuperPoint model_superpoint

A self-supervised framework for interest point detection and description in images, suitable for a large number of multiple-view geometry problems in computer vision

Feature Tracking Model: LightGlue model_lightglue

A model designed for efficient and accurate feature matching in computer vision tasks

Bird’s Eye View Perception: Fast-BEV model_fastbev

Obtaining a BEV perception is to gain a comprehensive understanding of the spatial layout and relationships between objects in a scene

Monocular Depth Estimation: Depth Anything V2 model_depthanythingv2

A powerful tool that leverages deep learning to infer 3D information from 2D images

The following pipelines were added:

Pipeline Name

Description

Diffusion Policy diffusion_policy

An innovative method for generating robot actions by conceptualizing visuomotor policy learning as a conditional denoising diffusion process

Robotics Diffusion Transformer (RDT) robotics_diffusion_transformer

A RDT pipeline provided for evaluating the VLA model on the simulation task

LLM Robotics Demo llm_robotics_demo

A code generation demo for robotics, interacting with a chatbot utilizing AI technologies such as large language models (Phi-4) and computer vision (SAM, CLIP)

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