Telekinesis Agentic Skill Library

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Telekinesis Agentic Skill LibraryBuild AI powered Computer Vision, Robotics and Physical AI applications.

Any robot. Any task. One Physical AI platform.

Quickstart
Create API Key

Cornea

Segment images using classical or deep learning models of your choice
Status: Released

Pupil

Perform image processing tasks and low-level vision algorithms
Status: Released

Vitreous

Process point clouds and build flexible 6D pose estimation pipelines
Status: Released

Retina

Detect objects in images using foundation models and classical algorithms
Status: Planned — Feb 2026

Illusion

Generate realistic datasets to train and validate vision and perception models
Status: Planned — Feb 2026

Iris

Train, fine tune, and deploy state-of-the-art deep learning models
Status: Planned — Feb 2026

Neuroplan

Use motion planning, kinematics, and control to run robots in simulation or the real world
Status: Planned — Feb 2026

Cortex

Build action graphs that combine primitive skills to generate robot motions
Status: Planned — Mar 2026

Brainwave

Design, simulate, and deploy complete end-to-end robotic solutions
Status: Planned — Apr 2026

Telekinesis Agentic Skill Library for Computer Vision, Robotics and Physical AI ​

Telekinesis Agentic Skill Library for Computer Vision, Robotics and Physical AI applications

The Telekinesis Agentic Skill Library is the first large-scale Python library for building agentic robotics, computer vision, and Physical AI systems. It provides:

  • Skills: a broad set of AI algorithms for perception, motion planning, and control.
  • Physical AI Agents: LLM/VLM agents for task planning across industrial, mobile, and humanoid robots.

The library is intended for robotics, computer vision, and research teams that want to:

  • Speed up development by integrating production-grade robotics, computer vision, and AI algorithms
  • Add intelligence to robots with LLM/VLM-driven task planning tied to real perception and control systems
  • Iterate quickly on Physical AI systems using a single, consistent Python library

Get started immediately with the Telekinesis Agentic Skill Library (Python 3.11 or 3.12):

python
pip install telekinesis-ai

💡 TIP

A free API_KEY is required.

Create one at platform.telekinesis.ai ↗.

See the Quickstart ↗ for more details.

Join our Discord community to add your own skills and be part of the Physical AI revolution!

What is a Skill? ​

A Skill is a reusable operation for robotics, computer vision, and Physical AI. Skills span 2D/3D perception (6D pose estimation, 2D/3D detection, segmentation, and image processing), motion planning (RRT*, motion generators, trajectory optimization), and motion control (model predictive control, reinforcement learning policies). Skills can be chained into pipelines to build real-world robotics applications.

Below are examples of what a Skill looks like:

Example 1: calculate_point_cloud_centroid. This skill calculates the centroid of a 3D point cloud.

python
# Example 1
from telekinesis import vitreous                                # Import Vitreous - 3D point cloud processing module

# Executing a 3D point cloud Skill
centroid = vitreous.calculate_point_cloud_centroid(             # Executing Skill - `calculate_point_cloud_centroid`
    point_cloud=point_cloud
)

Example 2: filter_image_using_gaussian_blur. A simple skill to apply Gaussian blur on an image.

python
# Example 2
from telekinesis import pupil                                   # Import Pupil - 2D image processing module                                                                        

# Executing a 2D image processing Skill
blurred_image = pupil.filter_image_using_gaussian_blur(         # Executing Skill - `filter_image_using_gaussian_blur`
    image=image,
    kernel_size=7,
    sigma_x=3.0,
    sigma_y=3.0,
    border_type="default",
)

Skills are organized in Skill Groups. Each Skill Group can be imported easily from the telekinesis library:

python
from telekinesis import vitreous  # point cloud processing skills
from telekinesis import retina    # object detection skills
from telekinesis import cornea    # image segmentation skills
from telekinesis import pupil     # image processing skills
from telekinesis import illusion  # synthetic data generation skills
from telekinesis import iris      # AI model training skills
from telekinesis import neuroplan # robotics skills
from telekinesis import medulla   # hardware communication skills
from telekinesis import cortex    # Physical AI agents
Cornea - Image segmentation skills
python
from telekinesis import cornea
  • Color-based segmentation: RGB, HSV, LAB, YCrCb
  • Region-based segmentation: Focus region, Watershed, Flood fill
  • Deep learning segmentation: BiRefNet (foreground), SAM
  • Graph-based segmentation: GrabCut
  • Superpixel segmentation: Felzenszwalb, SLIC
  • Filtering: Filter by area, color, mask
  • Thresholding: Global threshold, Otsu, Local, Yen, Adaptive, Laplacian-based
Pupil - Image processing skills
python
from telekinesis import pupil
  • Morphology: erode, dilate, open/close, gradient, top-hat
  • Structure: Frangi, Hessian, Sato, Meijering
  • Edges: Sobel, Scharr, Laplacian, Gabor
  • Denoising: Gaussian, median, bilateral, box filters
  • Enhancement: CLAHE, gamma correction, white balance
  • Transforms: pyramids, mask thinning

See all the Pupil Skills.

Vitreous - 3D point cloud processing skills
python
from telekinesis import vitreous
  • Point cloud: centroids, normals, bounding boxes, principal axes
  • Filtering: masks, outliers, downsampling, plane & cylinder removal
  • Segmentation: DBSCAN, density, color, plane-based clustering
  • Transforms: rigid transforms, scaling, projection
  • Registration: ICP (P2P, P2Plane), global registration, cuboid sampling
  • Meshes: shapes, mesh to point cloud, convex hull, Poisson reconstruction

See all the Vitreous Skills.

Retina - Object detection skills
python
from telekinesis import retina
  • Foundation-model based object detection
  • Classical object detection
Illusion - Synthetic data generation skills
python
from telekinesis import illusion
  • Synthetic image data generation for AI model training
Iris - AI Model training and deployment skills
python
from telekinesis import iris
  • AI model training pipelines
  • Fine-tuning and evaluation of foundation models
Neuroplan - Robotics skills
python
from telekinesis import neuroplan
  • Kinematics
  • Motion planning
  • Control
  • Robot database
Cortex - Physical AI Agents
python
from telekinesis import cortex
  • Action & Skill graphs
  • Physical AI Agents for skill graph generation and execution
Brainwave - Physical AI Platform
  • Skill & Agent orchestration
  • Simulation, digital twins, sim-to-real workflows
  • Monitoring and logging

What is a Physical AI Agent? ​

Recent advances in LLMs and VLMs, including systems such as LLama 4, Mistral, Qwen, Gemini Robotics, RT-2, π₀, world models, and Dream-based VLAs have shown the potential of learned models to perform semantic reasoning, task decomposition, and high-level planning from vision and language inputs.

In the Telekinesis library, a Physical AI Agent, typically a Vision Language Model (VLM) or Large Language Model (LLM), autonomously interprets natural language instructions and generates high-level Skill plans. In autonomous Physical AI systems, Agents continuously produce and execute Skill plans, allowing the system to operate with minimal human intervention.

To learn more about building the Telekinesis Physical AI Agents, explore Cortex.

How do Physical AI Agents use Skills to Perform Tasks? ​

Telekinesis Agentic Skill Library Architecture

Telekinesis Agentic Skill Library Architecture

Telekinesis Agentic Skill Library Architecture

Flow Overview

  1. A user prompts the robot with a task: "Hey, can you do a CNC machine loading task?"
  2. The Agent interprets the intent and reasons over the given task and sequencing.
  3. The Agent constructs a high-level plan and orchestrates the Skills — selecting order and parameters.
  4. Skills are executed on the robot using production-grade perception, motion, and control algorithms, with continuous feedback from the environment.

To understand the architectural motivations and system design of Telekinesis, read the Introduction.

What Can You Build? ​

Automated relay soldering powered by Physical AI

Telekinesis Agentic Skill Library helps you build real-world robotics and Physical AI applications for industries such as manufacturing, automotive, aerospace and others. We present some use cases in manufacturing which the Telekinesis team has already deployed using the skill library.

Automated Basil Harvesting

Build vision-based manipulation systems for agricultural robotics that operate reliably in unstructured outdoor environments.

With Telekinesis, detect plants, estimate grasp poses, and execute adaptive, closed-loop motions to safely handle delicate objects.

Carton Palletizing

Create vision-guided robotic palletizing systems that adapt dynamically to changing layouts and product variations in industrial automation environments.

Telekinesis enables object detection, pose estimation, and motion planning to work together for accurate placement across varying pallet configurations.

Lights-Out Laser Engraving

Develop fully autonomous robotic engraving systems using vision-based alignment and closed-loop execution.

With vision-based alignment and closed-loop execution, Telekinesis enables precise laser engraving even when part placement and orientation vary.

Automated Assembly

Build multi-step robotic assembly systems that combine task planning, coordinated manipulation, and precise motion execution.

Telekinesis allows perception, task coordination, and motion execution to be integrated into a single end-to-end assembly system.

Vision-Based Quality Control

Implement vision-based quality control and inspection pipelines using industrial computer vision for reliable defect detection and dimensional verification.

Using vision-based perception components, parts can be analyzed for surface defects, dimensional accuracy, or inconsistencies with repeatable results.

Start building your own use cases swiftly (Python 3.11 or 3.12):

python
pip install telekinesis-ai

💡 TIP

A free API_KEY needs to be obtained from platform.telekinesis.ai ↗.

See the Quickstart ↗ for more details.

Control Any Industrial Robot, Mobile Robot & Humanoid with a Unified Python Interface ​

One of the biggest pains of robotics is that each robot provider has their own interface to control their robots. We offer a skill group called neuroplan that provides a unified interface to control any industrial, mobile, or humanoid robot.

We currently support: Universal Robots (real & simulation), KUKA (real & simulation), ABB (real & simulation), Franka Emika (real & simulation), Boston Dynamics (simulation), Anybotics (simulation), Unitree (simulation).

python
from telekinesis import neuroplan # robotics skills

Prototype on any robot, perform any task on the same platform, and deploy the same Skill Groups anywhere - any robot, any task, on one Physical AI platform.

Learn more about the offered robotic skills in Neuroplan Overview.

Telekinesis Agentic Skill Library supports industrial, mobile and humanoid robots

Production-Grade Computer Vision Models for Robotics and Physical AI Systems ​

The library offers production-grade computer vision Skill Groups for object detection, segmentation, pose estimation, synthetic data generation and AI model training.

python
from telekinesis import vitreous  # point cloud processing skills
from telekinesis import retina    # object detection skills
from telekinesis import cornea    # image segmentation skills
from telekinesis import pupil     # image processing skills
from telekinesis import illusion  # synthetic data generation skills
from telekinesis import iris      # AI model training skills

from telekinesis import medulla   # sensor interface skills

Furthermore, we offer medulla which is a unified interface to cameras such as: Zivid, Mechmind, Microsoft Kinect, and others. Learn more in the Medulla Overview.

Computer Vision Skill Groups

2D Image Processing, Object Detection and Segmentation

Build reusable 2D vision pipelines using Pupil for low-level image processing, Retina for object detection, and Cornea for segmentation and mask generation.

These Skill Groups can be composed into standalone perception pipelines that operate on images, video streams, or sensor data—without requiring robot motion or control in the loop.

3D Point Cloud Processing & Mesh Generation

Develop geometric alignment pipelines using Vitreous to register point clouds or meshes against reference models or scenes.

Vitreous provides reusable registration Skills—such as ICP-based alignment and global registration—enabling precise localization, model-to-scene matching, and change detection in industrial inspection workflows.

3D Object Detection & 6D Pose Estimation

Create 3D object detection and 6D pose estimation pipelines by combining Retina for object detection with Vitreous for point cloud filtering, registration, and geometric pose estimation.

These Skill Groups enable object localization from point clouds or multi-view sensor data for downstream tasks such as grasp planning, inspection, and vision-guided manipulation.

Synthetic Data Generation & AI Model Training

Generate photo-realistic synthetic image datasets for training object detection, segmentation, and classification models using the Illusion skill group.

Train state-of-the-art AI models in the cloud on generated datasets and deploy them to real-world systems using the Iris skill group.

Computer Vision Skill Groups

Brainwave: the Telekinesis Physical AI Platform ​

Brainwave is the Telekinesis Physical AI cloud platform for managing skill orchestration, simulation, digital twins, and robot deployments from a single system. It enables agent-based robotics systems to be developed, deployed, and operated at scale across heterogeneous robots and tasks.

A first look at Brainwave - coming soon.

Telekinesis Physical AI Platform – Brainwave
Telekinesis Physical AI Platform: Brainwave

Develop and simulate digital twin workflows to validate, stress-test, and optimize Skill Groups. Deploy the same Skill Groups to real-world robots using a simulation-to-real transfer pipeline.

CNC Machine Tending

Pick and Place

Surface Polishing

Robotic Welding

Metal Palletizing

Palletizing

Developer Quickstart ​

You can easily integrate Telekinesis Agentic Skill Library into your own application. Setup the library in just 4 steps and start building!

Step 1: Generate an API Key ​

Since all the skills are hosted on the cloud, to access them securely, a free API key is needed. Create a Telekinesis account and generate an API key for free: Create a Telekinesis account!

Store the key in a safe location, such as your shell configuration file (e.g. .zshrc, .bashrc) or another secure location on your computer.

Step 2: Configure the API Key ​

Export the API key as an environment variable. Open a terminal window and run below command as per your OS system.

Replace <your_api_key> with the one generated in Step 1.

bash
export TELEKINESIS_API_KEY="<your_api_key>"
powershell
setx TELEKINESIS_API_KEY "<your_api_key>"

WARNING

For Windows, after running setx, restart the terminal for the changes to take effect.

The Telekinesis SDK uses this API key to authenticate requests and automatically reads it from your system environment.

Step 3: Pip Install the Telekinesis Agentic Skill Library ​

We currently support Python versions - 3.11, 3.12. Ensure your environment is in the specified Python version.

Install the core SDK using pip:

bash
pip install telekinesis-ai

Step 4: Run Your First Example ​

  1. Git clone our telekinesis-examples repository from Github with:
bash
git clone --depth 1 --recurse-submodules --shallow-submodules https://github.com/telekinesis-ai/telekinesis-examples.git

INFO

This also downloads the telekinesis-data repository, which contains sample data used by the examples. You can replace this with your own data when using Telekinesis in your own projects. Download time may vary depending on your internet connection.

  1. Change directory into telekinesis-examples:
bash
cd telekinesis-examples
  1. Install example-only dependencies:
bash
pip install numpy scipy opencv-python rerun-sdk==0.27.3 loguru
  1. Run the segment_image_using_sam example:
bash
python examples/cornea_examples.py --example segment_image_using_sam

If the example runs successfully, a Rerun visualization window will open showing the result.

INFO

Rerun is a visualization tool used to display 3D data and processing results.

Rerun Visualization

Sam Segmentation Demonstration

Join our Discord Community to Add your Own Skills ​

If you zoom out, the Telekinesis Agentic Skill Library and Brainwave are just the beginning.

OUR VISION

Our vision is to build a vibrant community of contributors who help grow the Physical AI Skill ecosystem.

We want you to join us. Maybe you’re a researcher who just published a paper and built some code you’re proud of. Maybe you’re a hobbyist tinkering with robots in your garage. Maybe you’re an engineer tackling tough automation challenges every day. Whatever your background, if you have a Skill, whether it’s a perception module, a motion planner, or a clever robot controller, we want to see it.

The idea is simple: release your Skill, let others use it, improve it, and see it deployed in real-world systems. Your work could go from a lab or workshop into factories, helping robots do things that were previously too dangerous, repetitive, or precise for humans.

Our vision is about building something practical, reusable, and meaningful. Together, we can make robotics software accessible, scalable, and trustworthy. And we’d love for you to be part of it.

Join our Discord community to be part of the Physical AI revolution!

What Next? ​

Explore all the features of Telekinesis Agentic Skill Library with Vitreous!