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SD PLATFORM AR-ASSISTED ROBOTIC ASSEMBLY (RECORDING)

£180.00£108.00

Recordings – 12 hours

Level: Beginners

Contact: info@soomeenhahm.com

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Description

 

AR-ASSISTED ROBOTIC ASSEMBLY in ARCHITECTURE

OBJECTIVE

The main objective of this course is to introduce the knowledge of exploring masonry structure assembly with industrial robots in the Augmented Reality (AR) environment. This course will introduce robotic concepts, AR concepts, and demonstrate how to develop an AR-assisted robotic assembly process that can be applied in architecture, construction or any creative field using a 6-axis industrial robot. At the same time, it helps students rethink the design and fabrication methods in the digital mind by finishing the process from parametric design to fabrication. The participants will be able to achieve the AR-assisted robotic operation simulation, interact with the industrial robot remotely, and assemble the parametric masonry structures they designed. This course will teach you how to parametrically design the structure, develop an AR-assisted robotic operation method, and transfer the commands to an industrial robot (Universal Robots UR10). This course will explain the design to the fabrication process, which has the potential to bridge the gap between parametric design and robotic production. The participants will master the skill of collaborative working, filtering of selective data and manipulation of data; and they will also learn the AR-assisted robotic operation method, which will be the beginning and foundation for students who want to learn and explore more about robotic production and digital fabrication in the future.

 

BRIEF

Day 1: (4h)
Beginner-level robotic operation method + Shape design algorithm
– Introduction of robotic fabrication
– Understanding of the basic Robots plugin user interface
– Basic operations (trajectory planning + pick and place)
– Shape design algorithm

Day 2: (4h)
Beginner-level Augmented Reality (AR) function + robotic assembly simulation
– Implementation of Maya polygon modelling techniques to develop a complex architectural geometry.
– Achieving parametric patterning on façade and landscape using Maya as well as building form detailing and materiality.
– Modelling simple interior details within the conceptual geometry.

Day 3: (4h)
Progress debugging+ Remote robotic operation + Final masonry structure assembly
– Remotely robotic operation
– Physical structure assembly

 

PARTICIPANTS

This course is for anyone interested in learning robotic fabrication and Augmented Reality. It is designed for beginner level participants and is suitable for those design students and professionals. You will need to install the software prior to the workshop: Rhino 7/ Robots / Fologram.

*No previous knowledge required.
Level: Beginners & Intermediate

 

APPLICATION FEE

£180 £108 
– It includes sample files of the course.

 

INSTRUCTOR

Yang Song (University of Liverpool)

Yang Song is an architectural student and a multidisciplinary designer who has been working for a number of years on projects that converge architecture design, augmented reality and digital fabrication. He has an M-Arch Degree in Architectural Design from the Bartlett School of Architecture, UCL. Yang Song, now, is a practice-based research PhD student at the Centre for Architecture and Visual Arts (CAVA), Liverpool School of Architecture, University of Liverpool. His PhD research aims to investigate workflow for an AR-assisted intuitive design to fabrication framework for robotic assembly. His framework will incorporate AR technology with real-time immersive design, robotic assembly method and human-robot interactions. Yang Song has published several academic conference and journal papers, and has given research presentations at related research conferences, including eCAADe, CAADRIA, SiGraDi, CDRF. He served as the AR and robotic workshop tutor at the University of Liverpool (UOL), SiGraDi 2021, and the dMA Leibniz University Hannover.

 

*In case of any issue regarding payment and application contact info@soomeenhahm.com

Additional information

SD Platform

Recordings

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