# Robotics AI Suite Edge AI Suites are collections of open, industry-specific AI software development kits (SDKs), microservices, and sample applications for independent software vendors (ISVs), system integrators and solution builders. The Robotics AI Suite is an open-source toolkit for developing robots that sense, interact, and make decisions at the edge. Built on a unified Intel platform, the Suite combines modular tools for vision, control, and AI inference, accelerating integration and deployment. Whatever your robotics workload - if you are bringing up a new platform, integrating sensors and actuators, or optimizing an AI workload with Intel - these documents help you find compatible ingredients and pipelines for your robotics application and guidance for deploying on Intel hardware. :::{image} ./edge-ai-suites/robotics-ai-suite/images/intro-light.png :class: only-light ::: :::{image} ./edge-ai-suites/robotics-ai-suite/images/intro-dark.png :class: only-dark ::: ## Industry Segments The Robotics AI Suite targets the following industry segments: - **[Autonomous Mobile Robot](./edge-ai-suites/robotics-ai-suite/hardware_blueprints/amr/index.md)**\ — Wheeled or tracked robots that navigate dynamic environments without fixed guidance, using onboard sensing, mapping, and path planning. Common in warehouse logistics, material transport, inspection, and last-mile delivery. - **[Humanoid](./edge-ai-suites/robotics-ai-suite/hardware_blueprints/humanoid/index.md)**\ — Human-shaped robots with articulated limbs designed to operate in spaces and with tools built for people. Used for manipulation, locomotion, and interactive tasks in service, research, and general-purpose automation. - **[Stationary Arm](./edge-ai-suites/robotics-ai-suite/hardware_blueprints/stationary_arm/index.md)**\ — Fixed-base robotic manipulators that perform precise, repeatable operations within a defined workspace. Typical applications include pick-and-place, assembly, welding, and machine tending on production lines. ## Reference Applications and Ingredients The table below lists the reference applications, sample pipelines, and tutorials available across this documentation. The **Domains** column categorizes each entry to help you find relevant material for your application. | Reference | Domains | Description | | --- | --- | --- | | [RealSense Camera with ROS 2 Sample Application](./edge-ai-suites/robotics-ai-suite/components/sensors/reference_applications/realsense-ros2.md) | Sensors, Middleware | Integrates an RealSense camera with ROS 2 to stream color and depth data, launch camera nodes, and visualize the feed in RViz2. | | [3D Pointcloud Groundfloor Segmentation for RealSense Camera and 3D LiDAR](./edge-ai-suites/robotics-ai-suite/components/sensors/reference_applications/pointcloud-groundfloor-segmentation.md) | Sensors, AI | Intel algorithm that classifies 3D point clouds from RealSense or LiDAR sensors into ground, elevated surfaces, and obstacles for navigation over challenging terrain. | | [Multi-Camera Object Detection Powered by OpenVINO™](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/reference_applications/openvino_multicam_demo.md) | AI, OpenVINO, Sensors | Runs OpenVINO™-optimized YOLOv8 object detection and segmentation in parallel across up to four USB or GMSL cameras. | | [OpenVINO™ Object Detection Tutorial](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/reference_applications/object_detection_tutorial.md) | AI, OpenVINO, Sensors, Middleware | Deploys a ROS 2 OpenVINO™ node for object detection with selectable CPU, GPU, or NPU inference devices. | | [OpenVINO™ Yolov8 Tutorial](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/reference_applications/yolov8_openvino_tutorial.md) | AI, OpenVINO, Sensors, Middleware | Installs a ROS 2 OpenVINO™ node and runs a YOLOv8 segmentation model on the CPU using a RealSense camera image as input. | | [OpenVINO™ Tutorial with Segmentation](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/reference_applications/segmentation_realsense_tutorial.md) | AI, OpenVINO, Sensors, Middleware | Runs a ROS 2 OpenVINO™ semantic segmentation model on CPU or GPU using a RealSense camera image as input. | | [Collaborative Visual SLAM](./edge-ai-suites/robotics-ai-suite/components/optimized_solutions/collaborative-slam.md) | Autonomous Mobile Robot, SLAM | Multi-robot visual SLAM optimized with SSE/AVX2 instruction sets for map building and merging on Intel® CPUs and GPUs. | | [FastMapping Algorithm](./edge-ai-suites/robotics-ai-suite/components/optimized_solutions/run-fastmapping-algorithm.md) | Autonomous Mobile Robot, Sensors | Intel-optimized octomap implementation that builds 3D voxel maps from RealSense depth camera data for efficient environment representation. | | [ADBSCAN Follow-me](./edge-ai-suites/robotics-ai-suite/components/optimized_solutions/adbscan-follow-me.md) | Autonomous Mobile Robot, AI, Sensors | Adaptive DBSCAN person detection and tracking from 2D/3D LiDAR or RealSense point clouds, with Gazebo simulation and real-robot deployment examples. | | [ITS Path Planner ROS 2 Navigation Plugin](./edge-ai-suites/robotics-ai-suite/components/optimized_solutions/its-path-planner-plugin.md) | Autonomous Mobile Robot, Navigation | Intel patented global path planner delivering 20-30x speedup over A* for the ROS 2 Navigation2 stack. | | [Robot Re-localization Package for ROS 2 Navigation](./edge-ai-suites/robotics-ai-suite/components/optimized_solutions/navigation-relocalization.md) | Autonomous Mobile Robot, Navigation | Re-localization algorithm that rapidly recovers robot pose in Nav2 after sensor glitches or environment disturbances. | | [GPU ORB Extractor](./edge-ai-suites/robotics-ai-suite/components/optimized_solutions/orb-extractor.md) | Autonomous Mobile Robot, SLAM | GPU-accelerated keypoint and descriptor extraction for Visual SLAM front-ends, with OpenCV and OpenCV-free APIs. | | [Deploy Robot Teleop Using a Keyboard](./edge-ai-suites/robotics-ai-suite/software_references/amr/deployment/teleop_deploy.md) | Autonomous Mobile Robot | Validates motor control on a deployed robot using keyboard teleoperation before running autonomous workloads. | | [Deploying `wandering`](./edge-ai-suites/robotics-ai-suite/software_references/amr/deployment/wandering_deploy.md) | Autonomous Mobile Robot, Navigation | Deploys the Wandering autonomous exploration pipeline on a physical robot using RTAB-Map and Nav2. | | [Simulated Robotics with Gazebo](./edge-ai-suites/robotics-ai-suite/software_references/amr/simulation/basic_sim.md) | Autonomous Mobile Robot, Simulation | Introduces simulating robots as digital twins in Gazebo to test robotics applications before real-world deployment. | | [Simulating `wandering` in Gazebo](./edge-ai-suites/robotics-ai-suite/software_references/amr/simulation/wandering_sim.md) | Autonomous Mobile Robot, Simulation, Navigation | Simulates the full Wandering pipeline in Gazebo with mapping, frontier exploration, and Nav2-based navigation. | | [Gazebo Pick & Place Demo](./edge-ai-suites/robotics-ai-suite/components/middleware/gazebo/reference_applications/picknplace.md) | Middleware, Manipulation, Simulation | Coordinates two UR5 arms and a TurtleBot3 AMR on a conveyor line using MoveIt2 and Nav2 in Gazebo Classic. | | [Imitation Learning - ACT](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/imitation_learning_act.md) | Humanoid, AI, OpenVINO, Manipulation | Imitation learning pipeline using Action Chunking with Transformers, optimized with OpenVINO™, for fine manipulation in simulation and on real ALOHA robots. | | [Model Predictive Control Demo](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/mpc_demo.md) | Humanoid, AI, Manipulation | Combines ACT imitation learning with OCS2 model predictive control and MuJoCo simulation for perception-action manipulation control. | | [Diffusion Policy](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/diffusion_policy.md) | Humanoid, AI, OpenVINO, Manipulation | Visuomotor diffusion-policy pipeline for the Push-T manipulation task, with Transformer- and CNN-based variants optimized by OpenVINO™. | | [VSLAM: ORB-SLAM3](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/ORB_VSLAM.md) | Humanoid, SLAM | Real-time feature-based Visual SLAM supporting monocular, stereo, and RGB-D cameras, with EUROC dataset and RealSense demos. | | [LLM Robotics Demo](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/llm_robotics.md) | Humanoid, AI, Manipulation | Code-generation pipeline combining an LLM (Phi-4), vision models (SAM, CLIP), and a JAKA arm for voice- or text-commanded robot control. | | [Robotics Diffusion Transformer (RDT)](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/robotics_diffusion_transformer.md) | Humanoid, AI, OpenVINO, Manipulation | Bimanual manipulation foundation model with a unified action space, running in MuJoCo simulation and on real ALOHA robots with OpenVINO™ optimization. | | [Pi0.5 with Real-Time Chunking](./edge-ai-suites/robotics-ai-suite/software_references/humanoid/sample_pipelines/pi05_with_rtc.md) | Humanoid, AI, OpenVINO, Manipulation | Vision-Language-Action pipeline pairing a PaliGemma VLM with a flow-matching policy and real-time chunking for smooth high-frequency control, accelerated with OpenVINO™. | | [Action Chunking with Transformers - ACT](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_act.md) | AI, OpenVINO, Manipulation | Imitation learning model that predicts action chunks with Transformers for fine manipulation, including conversion to OpenVINO™ IR. | | [Diffusion Policy (Model)](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_dp.md) | AI, OpenVINO, Manipulation | Visuomotor policy using conditional denoising diffusion to handle multimodal action distributions, with low-dim and image variants and OpenVINO™ conversion. | | [Robotics Diffusion Transformer (RDT-1B)](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_rdt.md) | AI, OpenVINO, Manipulation | 1.2B-parameter diffusion foundation model for manipulation pre-trained on 46 datasets, with OpenVINO™ IR conversion guidance. | | [General-purpose robot foundation model (Pi0)](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_pi0.md) | AI, OpenVINO, Manipulation | Vision-Language-Action foundation model pairing a PaliGemma VLM with an action-expert diffusion transformer, including OpenVINO™ conversion. | | [BC-RNN & BC-Transformer](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_bc_rnn.md) | AI, OpenVINO, Manipulation | Behavior cloning models using RNN or Transformer backbones to map observations to actions from expert demonstrations. | | [Visual Servoing - CNS](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_cns.md) | AI, OpenVINO, Manipulation | Graph neural network image-based visual servo policy achieving sub-millimeter precision at real-time (~40 fps) rates. | | [GraspNet - Baseline](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_graspnet.md) | AI, OpenVINO, Manipulation | Grasp generation model trained on GraspNet-1Billion that predicts scored 6-DoF grasp poses from point clouds. | | [Feature Extraction Model: SuperPoint](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_superpoint.md) | AI, OpenVINO, SLAM | Self-supervised interest point detector and descriptor generator with homographic adaptation for cross-domain generalization. | | [Feature Tracking Model: LightGlue](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_lightglue.md) | AI, OpenVINO, SLAM | Lightweight transformer feature matcher with adaptive depth and width for efficient correspondence in 3D reconstruction and localization. | | [Improved 3D Diffusion Policy (iDP3)](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_idp3.md) | AI, OpenVINO, Manipulation | Enhanced 3D manipulation policy that encodes point clouds with a 3D visual encoder and generates actions via diffusion. | | [Bird's Eye View Perception: Fast-BEV](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_fastbev.md) | AI, OpenVINO, Navigation | Efficient multi-scale bird's-eye-view perception model for obstacle avoidance, path planning, and spatial awareness. | | [Monocular Depth Estimation: Depth Anything V2](./edge-ai-suites/robotics-ai-suite/components/ai_resources/openvino/models/model_depthanythingv2.md) | AI, OpenVINO, Sensors | Monocular depth estimation foundation model (25M-1.3B parameters) for cost-effective depth perception without LiDAR. | | [Wandering AMR Pipeline Benchmark](./edge-ai-suites/robotics-ai-suite/components/benchmarking/robotics-system-profiler/wandering-benchmark.md) | Benchmarking, Autonomous Mobile Robot | Automated benchmarking of the Wandering AMR pipeline, measuring latency, resource usage, and optional GPU/NPU KPIs across runs. | | [Pick & Place Pipeline Benchmark](./edge-ai-suites/robotics-ai-suite/components/benchmarking/robotics-system-profiler/picknplace-benchmark.md) | Benchmarking, Manipulation | Automated benchmarking of the multi-robot Pick & Place simulation, capturing lifecycle metrics and aggregated KPIs. | ## Explore Intel Robotics Ecosystem [Scale Enablement - Robotics Builders Community | Intel(R) Industry Solution Builders](https://builders.intel.com/communities/robotics/scale) Explore robotics Scale Enablement and discover how Intel's ecosystem and experts help accelerate robotics solutions from design to deployment. [Edge AI Partner Spotlight - Solution Hub | Intel(R) Industry Solution Builders](https://builders.intel.com/ecosystem-engagement/solution-hub/edge-ai-catalog/partner-spotlight?cp=53&cid=202&type=system) Browse our curated catalog of Intel-powered Edge AI systems and applications, delivering real-time innovation, efficiency, and intelligence to your business. ## Next Steps Continue to the System Requirements guide to learn about supported Intel processors, OS requirements, and development kits: - **[System Requirements](./edge-ai-suites/robotics-ai-suite/platform_foundation/system_requirements.md)** — select a platform and install an OS distribution.  :::{toctree} :caption: Platform Foundation :hidden: System Requirements Getting Started ::: :::{toctree} :caption: Components :hidden: Intel Optimized Robotics Solutions and Ingredients Real-time Determinism Benchmarking Security Middleware Sensors AI Resources Physical AI Studio ::: :::{toctree} :caption: Hardware Blueprints :hidden: Autonomous Mobile Robot Humanoid Robot Stationary Arm ::: :::{toctree} :caption: Software References :hidden: Autonomous Mobile Robot Humanoid Robot Stationary Arm ::: :::{toctree} :caption: Resources :hidden: Migrating from NVIDIA Heterogeneous Computing Release Notes Troubleshooting Glossary Get Help or Contribute :::