What will this workshop teach me?

You’ll learn how to turn scanned irregular objects into surface-aware robotic toolpaths for applications such as 3D printing, milling, and coating.

Do I need to know Rhino and Grasshopper before joining?

The workshop uses Rhino 8 and Grasshopper, so familiarity with these tools would be helpful for following the technical workflows.

Will the workshop cover real-world, irregular geometry?

Yes, the workshop focuses specifically on scanned and noisy geometry rather than perfect digital models, teaching you how to create toolpaths that adapt to complex surfaces.

Which software and tools will be used?

You’ll work with Rhino 8, Grasshopper, the Robots plugin, and Google Colab for digitization, toolpath generation, and robotic simulation.

Will I learn how to validate robotic toolpaths before fabrication?

Yes, you’ll simulate the robot’s movements to check reachability, collisions, joint limits, and singularities before physical execution.

Full Access Workshop Feb 28 – Mar 1, 2026 8 Hours

Robotic Fabrication for Irregular Geometry

Name: Robotic Fabrication for Irregular Geometry
Price: 93.50 EUR
Availability: InStock

This workshop focuses on scan-to-robot workflows, generating surface-aware robotic toolpaths from irregular geometry and validating them through kinematic simulation.

Zvonko Vugreshek

Verified Account

3 courses5.0

About Robotic Fabrication for Irregular Geometry

Most robotic fabrication tutorials assume that you are starting with a perfect digital model. However, the future of construction and manufacturing involves interacting with irregular and 'messy' real-world objects, or digital captures of them.

In this technical workshop, we will explore the latest frameworks for digitising complex objects and generating complex, surface-aware robotic toolpaths that adapt to their unique topology.

This workshop provides an in-depth exploration of the generation of computational toolpaths. The technical workflows required to generate valid instructions for any robot will be covered.

Input: We will use automated computer vision to digitise a physical object.
Process: The geometry will be processed by Grasshopper to create suitable toolpaths.
Output: We will validate these paths using a kinematic simulation (Robots plugin) to ensure they can be executed without issue.

What you will learn

Mastering computational concepts for managing complex toolpath arrays.
Understanding robot kinematics and how to visualise and validate reachability.
Mesh-to-Path Logic: Techniques for projecting vector paths onto 'noisy' scanned meshes.
Simulation & Safety: Verifying toolpaths digitally to prevent physical crashes (singularity analysis).
Machine Code Generation: Learn how to export your design as code that robots can read.

Methodology

Digitisation (the input): We will use a streamlined 'scan-to-mesh' workflow using computer vision tools to instantly create a 3D digital twin of a physical object from an image.
Toolpath Logic (the core): We will develop parametric scripts to generate 'surface following' paths (e.g., for 3D printing or milling) that hug the geometry.
Kinematics (The Validation): We will simulate the robot's motion to check reachability, collisions, and joint limits using the Robots plugin.

Program:

Day 1 - From Scan to Surface

First step: Extract 3D models of objects from images using computer vision tools.
Second step: Mesh clean-up and rationalisation in Rhino 8.
Third step: Generating toolpaths on the geometry to guide the robot.

Day 2 - The 'Robotic Hand' (Toolpathing & Simulation):

Import the 'digital twin' into the robotic environment.
Generate a toolpath for 3D printing, milling, or coating that adapts to the unique geometry of the object.
Use the Robots plugin to simulate the execution of the robotic arm.
If time allows, run it on a real robot.

Course Content

11 Lessons

Screenshots

Software & tools

Highlights

Instructors

Zvonko Vugreshek

3 Courses5.0

Zvonko is an architect turned engineer and digital fabricator. He is currently addressing the challenge of integrating data science and machine learning into design and fabrication processes. He is working on his company, Pixolid UG, which operates in these fields, in Berlin. Zvonko has also been active in academia, working as a researcher and lecturer at various universities in Berlin and the surrounding area, including TU Berlin, BTU Cottbus, and IU Berlin, in the fields of digital fabrication, robotics, and computational/generative design.

His work focuses on bridging the gap between digital models and physical realities by training models to enhance robot-to-robot and human-to-robot collaboration. In this workshop, he will share his experience of translating real-world objects from photographs and demonstrate how computer vision and adaptive toolpaths can transform fabrication and design workflows.

Robotic Fabrication for Irregular Geometry FAQ

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