Robot API and SDK Directory (2026): Every Major Platform for Developers
The robot development tooling landscape is confusing. There are platform SDKs (NVIDIA Isaac), robot operating systems (ROS 2), manufacturer SDKs (Unitree, UFACTORY), AI training frameworks (LeRobot, Isaac Lab), and cloud platforms. This directory lists every major option, what it does, and when you need it.
Use this as a reference when starting a new robotics project. Each entry tells you what the tool does, what license it uses, and where to get it.
Platform-level SDKs
These provide comprehensive robot development environments, not just a single library.
NVIDIA Isaac
| Aspect | Details |
|---|---|
| What | Full-stack robot development platform: simulation, training, deployment |
| Components | Isaac Sim, Isaac Lab, Isaac ROS, Isaac GR00T, Cosmos |
| License | Free for development (GPU hardware required) |
| Languages | Python, C++ |
| Hardware req. | NVIDIA GPU (RTX 3070+ for Sim, Jetson for deployment) |
| Link | developer.nvidia.com/isaac |
| Best for | Teams building serious AI-powered robots with NVIDIA hardware |
The most comprehensive platform available. Covers everything from simulation through training to edge deployment. Overkill for hobby projects, essential for production robots. See our NVIDIA Isaac vs Cosmos guide for how the components fit together.
Hugging Face LeRobot
| Aspect | Details |
|---|---|
| What | Open-source framework for robot learning: data collection, training, deployment |
| Components | Teleoperation, dataset management, imitation learning, pre-trained policies |
| License | Apache 2.0 |
| Languages | Python |
| Hardware req. | Any computer (CPU works, GPU recommended for training) |
| Link | github.com/huggingface/lerobot |
| Best for | Researchers, learners, anyone starting with affordable robot arms |
The fastest way to go from zero to autonomous robot manipulation. Designed around the SO-101 arm but supports other hardware. Includes pre-trained VLA models (ACT, pi-zero, SmolVLA) that work out of the box. See our Best Affordable Robot Arms guide for compatible hardware.
ROS 2 (Robot Operating System)
| Aspect | Details |
|---|---|
| What | Middleware framework for robot software: communication, coordination, tools |
| Components | pub/sub messaging, tf2 (transforms), nav2 (navigation), MoveIt2 (manipulation) |
| License | Apache 2.0 |
| Languages | Python, C++ |
| Hardware req. | Linux (Ubuntu recommended), some Windows/macOS support |
| Link | ros.org |
| Best for | Any multi-component robot system that needs standardized communication |
The industry standard for robot software integration. Not an AI framework, a communication and coordination layer that everything else plugs into. Most manufacturer SDKs offer ROS 2 bridges. Most NVIDIA Isaac tools integrate with ROS 2 natively.
Manufacturer SDKs
These come from robot hardware companies and provide control over their specific platforms.
Unitree SDK 2
| Aspect | Details |
|---|---|
| What | Official SDK for Unitree robots (G1, H2, Go2, B2) |
| License | Proprietary (free to use with Unitree hardware) |
| Languages | Python, C++ |
| Link | github.com/unitreerobotics/unitree_sdk2 |
| Features | Low-level motor control, high-level locomotion API, ROS 2 bridge |
| Best for | Anyone building on Unitree hardware |
Also notable: Unitree maintains a LeRobot integration (unitree_IL_lerobot) for using Hugging Face’s imitation learning framework directly with G1’s dual-arm dexterous hands.
UFACTORY xArm SDK
| Aspect | Details |
|---|---|
| What | Official SDK for UFACTORY xArm robot arms |
| License | BSD (open-source) |
| Languages | Python, C++, ROS 2 |
| Link | github.com/xArm-Developer |
| Features | Joint/Cartesian control, force sensing, gripper control, collision detection |
| Best for | Anyone using xArm hardware for research or production |
Dobot SDK
| Aspect | Details |
|---|---|
| What | Official SDK for Dobot robot arms (Nova, CR, MG400) |
| License | Proprietary (free with Dobot hardware) |
| Languages | Python, C++, C#, Java |
| Link | github.com/Dobot-Arm |
| Features | TCP/IP control, graphical programming (Dobot+), ROS integration |
| Best for | Education, light automation with Dobot hardware |
AI and Training Frameworks
These provide the machine learning infrastructure for training robot policies.
NVIDIA Isaac Lab
| Aspect | Details |
|---|---|
| What | GPU-accelerated framework for robot reinforcement and imitation learning |
| License | MIT (open-source) |
| Languages | Python |
| Hardware req. | NVIDIA GPU (runs thousands of parallel environments) |
| Link | github.com/isaac-sim/IsaacLab |
| Best for | Training locomotion and manipulation policies at scale |
NVIDIA Isaac GR00T
| Aspect | Details |
|---|---|
| What | End-to-end humanoid development platform with pre-trained VLA model |
| License | Open (specific terms per version) |
| Current version | GR00T 1.7 (Cosmos-Reason2-2B backbone, 32K hours real + 8K hours sim training) |
| Link | developer.nvidia.com/isaac/groot |
| Best for | Humanoid robot developers who want a ready-made VLA foundation |
MuJoCo
| Aspect | Details |
|---|---|
| What | Physics simulator optimized for robot control and reinforcement learning |
| License | Apache 2.0 (open-source since 2022, originally DeepMind) |
| Languages | Python (via mujoco-py), C |
| Link | mujoco.org |
| Best for | RL researchers, fast physics simulation, contact-rich manipulation |
Lighter and faster than Isaac Sim but less photorealistic. Often used for rapid policy iteration before transferring to Isaac Sim for visual fidelity testing.
PyBullet
| Aspect | Details |
|---|---|
| What | Open-source physics engine for robot simulation and RL |
| License | zlib (very permissive) |
| Languages | Python, C++ |
| Link | pybullet.org |
| Best for | Quick prototyping, academic research, when you need something simpler than Isaac Sim |
Older and less maintained than MuJoCo or Isaac Sim, but still widely used in academic RL research due to simplicity and good documentation.
Cloud and Deployment
NVIDIA Jetson (edge deployment)
| Aspect | Details |
|---|---|
| What | Edge AI compute modules for deploying trained models on real robots |
| Products | Jetson Orin Nano ($249), Jetson Orin NX ($599), Jetson Thor (upcoming) |
| Best for | Running trained policies on-robot without cloud connectivity |
Jetson Thor is specifically designed for humanoid robots, providing the onboard compute for running GR00T policies locally.
Foxglove
| Aspect | Details |
|---|---|
| What | Visualization and debugging platform for robotics data |
| License | MIT (core), commercial (cloud features) |
| Link | foxglove.dev |
| Best for | Debugging robot behavior, visualizing sensor data, log analysis |
The modern replacement for RViz (ROS’s built-in visualizer). Web-based, supports ROS 2 natively, and handles large datasets better.
Decision matrix
| Your situation | Primary tool | Supporting tools |
|---|---|---|
| Learning physical AI from scratch | LeRobot + SO-101 | ROS 2 (later) |
| Building a humanoid with Unitree hardware | Isaac GR00T + Unitree SDK | Isaac Sim, ROS 2 |
| Training manipulation policies | Isaac Lab | MuJoCo (prototyping), Isaac Sim (validation) |
| Deploying perception on a mobile robot | Isaac ROS | ROS 2, Jetson |
| Building a product with an xArm | xArm SDK + ROS 2 | Isaac Sim (for testing) |
| Academic RL research | MuJoCo or PyBullet | Isaac Lab (for scale) |
FAQ
Do I need ROS 2 for every robot project?
No. ROS 2 is most valuable when your robot has multiple subsystems that need to communicate (cameras, arms, navigation, planning). For a single robot arm running a learned policy, LeRobot or a manufacturer SDK is simpler. ROS 2 becomes essential as system complexity grows.
Is NVIDIA Isaac free?
Yes for development. All Isaac components (Sim, Lab, ROS, GR00T models) are free to download. You pay only for NVIDIA GPU hardware. There are no per-robot licensing fees for deployment.
Can I mix tools from different ecosystems?
Yes. ROS 2 is the common integration layer. A typical project might use: Isaac Sim for simulation, LeRobot for data collection, Isaac Lab for training, Unitree SDK for hardware control, and ROS 2 to connect everything. Cross-ecosystem interoperability is the norm, not the exception.
What if I do not have an NVIDIA GPU?
LeRobot works on CPU (slower training but functional). MuJoCo and PyBullet work without NVIDIA hardware. Isaac Sim and Isaac Lab require NVIDIA GPUs. For serious physical AI development, an NVIDIA GPU is a near-requirement in 2026.
Which tool should I learn first?
If you are new to robotics: LeRobot (immediate hands-on results). If you already know robotics and want to add AI: Isaac Lab. If you are building a production system: ROS 2 first, then layer in AI tools.