Design and Construction of an Innovative Pavilion Using
Topological Optimization and Robotic Fabrication
Ding Wen BAOa,b, Xin YANa,c, Roland SNOOKSb, Yi Min XIEa,d,*
a,* Centre for Innovative Structures and Materials, School of Engineering, RMIT University,
Melbourne, 3001, Australia
b School of Architecture and Urban Design, RMIT University,
Melbourne, 3001, Australia
c Centre of Architecture Research and Design, University of Chinese Academy of Sciences,
Beijing, 100190, China
d XIE Archi-Structure Design, Shanghai, 200092, China
This research explores innovations in structural design and construction through the generative design
technique BESO (Bi-directional Evolutionary Structural Optimization)  and the application of robotic
fabrication to produce efficient and elegant spatial structures. The innovative pavilion discussed in this
paper demonstrates a design and fabrication process and the collaboration between architecture and
engineering research groups through a series of small-scale test models and a full-scale model of
topologically optimized spatial structures. The focus of this work is the use of a modified BESO
technique to optimize the structure which features branches of various sizes, inspired by Gaudi’s
Sagrada Familia Bacilica, and the introduction of large-scale robotic 3D printing developed at RMIT
University. The advantages of the new design and construction process are efficient material usage and
elegant structural forms.
Keywords: topological optimization, multi-agent, robotic fabrication, prefabricated building, pavilion, mass
Throughout the history of architecture, the expression of building form has been limited by traditional
building method, in which even slightly irregular forms can significantly change the time and cost
needed for construction . However, Since the introduction of computational aided design technology
into the architectural design at the end of the 20th century, the topic of form-finding based on structural
performance has gained new momentum . The development of architectural technology is closely
related to the evolution of structural morphology, from barrel arches and domes in the period of Greece
and Rome to pendentives and flying buttresses in the period of Byzantium and Gothic; from physical
models used by Antonio Gaudi and Frey Otto to the application of topological optimization technology
to architectural designs, architectural morphology and structural optimization have always been
reinforcing each other.
The Bi-directional Evolutionary Structural Optimization (BESO) method  is one of the most popular
techniques for topology optimization. With the further enhancement of the BESO technique by Mike
Xie and his team, more and more architects will have opportunities to use a new intelligent method to
work with the computer interactively, to create innovative, efficient and organic architectural forms and
facilitate the realization of mass customization in the construction industry through the introduction of
Article published in
Proceedings of IASS Annual Symposium 2019 (5), 1-8
advanced 3D printing technologies, such as large robotic 3D printing and some hybrid fabrication
strategies developed by Roland Snook and his research team in RMIT Architectural Robotic Lab. The
concept of topological optimization and the inspiration of Gaudi’s Sagrada Familia Basilica will be
reflected through the pavilion form-finding and its optimization. The new approach of generative
architectural design and fabrication will be introduced in this project, which explores the architectural
implications of topological optimization design through robotic 3D fabrication.
2. Morphological conditioned design based BESO method
Using the BESO method, architects and engineers can generate many elegant and organic forms with
high structural performance. However, there are always inevitable constraints besides structure behavior,
such as functional requirements, construction limitations and aesthetic preference. As a result, it is
necessary to add some controlling methods into BESO process to obtain a form which can meet
composite demand. In this work, three main morphological conditioned design methods are introduced.
2.1. Geometrical restriction
In many practical projects, the geometrical restriction method is the most convenient and effective way
for designers to modify BESO results with some functional requirements manually and explicitly. For
functional cavities, like corridors and windows, they should be dug out of the geometries before
generating the calculating meshes and functional solids can be also reserved in BESO process by setting
them as the non-design domain. For example, the original design domain showed in Figure 1(a) without
any modification generates the form in Figure 1(c). However, with setting the functional cavity and non-
design domain into the model before calculation, the final design can be partly manipulated by designers
intently Figure 1(b) .
2.2. Properties influence
Another way to indirectly influence the BESO result is to set the material properties and evolutionary
parameters. With the different relative material Young’s modulus, the distribution density of BESO
structures between the two materials can be designed purposefully . For example, Figure 2(a) shows
a façade model with the bottom boundaries fixed in all displacements and pressure acted on the top
boundaries. And the optimized structures vary significantly with the different material properties of the
top boundaries (blue areas in Figure 2).
(a) (b) (c)
Figure1: The geometrical restriction in BESO method
(a) (b) (c)
Figure 2: Façade optimized structure with different relative material properties:
(a)the load conditions; (b) the BESO result with solid material in non-design domain; (c) the BESO result with
soft material in non-design domain
2.3. Prototype inspiration
Gaudi’s understanding of ‘structural optimization’ in natural form and his strategy of physical structural
modeling are very conceptually close to the principle of BESO and BESO’s logic of form finding 
(Figure 3). As an evolutionary algorithm BESO can not only generate forms independently, but also
collaborate with other prototyping techniques in optimization process. The well-known Sagrada Familia
in Barcelona is designed based on anti-hanging physical models by Anthony Gaudi. As a result, using a
new topology optimization tool Ameba , this work integrates BESO method with Gaudi’s prototyping
strategy to obtain innovative structure/ pavilion (Figure 4)
Figure 3: The similarities between Sagrada Familia Basilica and pavilion’s top and columns by BESO method
Figure 4: The process of Sagrada Familia inspired pavilion design by BESO topological optimization method
3. Large advanced automated robotic arm 3D printing process
3.1. Application of KUKA Robotic Fabrication
The Advanced Manufacturing Precinct at RMIT University hosts a range of 3D printers for metallic and
polymeric materials and in the Architectural Robotics Lab there are several Kuka robots with various
functions (Figure 5)
Figure 5: RMIT Architectural Robotic Lab
These new techniques for 3D printing fireproof polymer developed by Roland Snooks and his team at
RMIT architecture, are now being used to build structures that can meet building code, which is used in
the National Gallery of Victoria (NGV) interior pavilion panels and partition wall of Monash University
SensiLab (Figure 6).
Figure 6: Monash SensiLab and NGV Floe pavilion
It is an innovative technology combination of KUKA 6 axis robot fitted with a plastic extruder that
designed for building scale prefabricated architectural components, compared with the significant
limitations of traditional small-scale plastic 3D printing (Figure.7).
Figure 7(a): Small Scale Desktop 3D printer (printing area: 200mm x 200mm x 300mm)
Figure 7(b): Large Robotic 3D printer (printing area: 800mm x 1000mm x 1800mm)
3.2. Code development for printing fractal-like geometries
The whole tree branches system of the pavilion columns comprises four main translucent tree branches-
like polymer columns printed by a desktop printer first (Figure 8) then by a large robotic printer.
Figure 8: 3D printing model testing by small scale desktop 3D printer
The updated code of printing path helps robotic to achieve the aim of printing fractal-like geometries
rather than non-stop and one-curve printing path through introduction “start-stop” script into the original
printing C# code (Figures 9 and 10).
Figure 9: The process of robotic large 3D printing, using the updated code for project exhibited in Hong Kong
Figure 10: Grasshopper simulation of robotic printing path
(red ones are extruded path & blue ones are non-extruded path)
3.3. Testing of polymer materials for 3D printing quality
Material behavior in printing process is another issue that is hard to control. In this work, the relationship
between printing parameters and material stiffness is explored with a series of trials of fractal-like
geometries (Figure 11). From table 1, stability of printing will be significantly influenced by printing
speed once it is more than 200 mm/s; the Z height impacts the stability and speed of printing; and bead
size will cause the thickness of extrusion; one of the most influent parameters is extrude temperature, it
significantly effects the transparency of printing result. Thus, the most successful result is with the 60
mm/s, 2.8 mm Z-height, 4.2 bead size and 210 degree extrude temperature.
Figure 11: Printing example with various qualities (from left to right: bad to good printing qualities)
Table 1: Testing results of polymer materials with various parameters
3.4. Printing Constraints
Current technique has some printing limitation by the issue of large overhang angles without any
supporting material (Figure 12).Therefore a new BESO algorithm is currently being developed to
resolve this issue in the near future.
Figure 12: The result of overhang angles issue in digital and printed models: red part in digital model (left) is
over 32-degree overhang angles that fail to print showing in physical models (right)
This innovative pavilion is a demonstration of the combination of new design and construction
techniques, explaining the design and construct process of the pavilion through exploration of emerging
technologies in both digital design and advanced manufacturing, which are respectively topology
optimization-based form-finding and large-scale robotic 3D printing.
The testing results from a series of prototypes clearly illustrate that the optimized structures may play a
useful role in architectural form exploration or provide inspirations for it. The Bi-directional
Evolutionary Structural Optimization (BESO) method provides many possibilities in the process of
creating innovative and efficient forms. Each geometrical restriction, different material properties and
algorithmic parameter may result in different forms, meeting various requirements set by the user.
Also, compared with the traditional small-scale fused deposition modeling (FDM) 3D printing, robotic
3D printing has much greater potential to serve the building industry due to its capability of producing
large-scale printed architectural components with high structural performance.
However, major barriers to the implementation of these technologies in the building industry include a
lack of compression and strength test, UV degradation of the printed polymer components as well as the
significant issue of printing overhang angle, even though some of such printed structures have passed
the fire testing and building codes in Australia as well as partially been put into use. In this present study,
some of the advantages and insufficiencies of the new techniques have been examined. Much more
research and improvement are required in the future. Once the aforementioned issues are resolved, these
new technologies could be widely applied to the mass customized design and manufacturing in the
The authors would like to thank several colleagues whose support helped fulfill the research project
described in this paper:
•Mr. Charlie Boman and Mr. Hesam Mohamed (Snooks Research Lab, RMIT)
•Mr. Yulin Xiong (Centre for Innovative Structures and Materials, RMIT)
 X. Huang, Y. M. Xie, Evolutionary Topology Optimization of Continuum Structures: Methods
and Applications. Chichester: Wiley, 2010
K. G. Lee and J. S. Sun, “Clay Robotics,” Robotic Futures, Tongji University Press, pp. 113-
Y. M. Xie, Z. H. Zuo, X. Huang, T. Black and P. Felicetti, “Application of Topological
Optimization Technology to Bridge Design,” Structural Engineering International, vol. 24, pp.
K. Yang, Z.-L. Zhao, Y. He, S. Zhou, Q. Zhou, W. Huang and Y. M. Xie, “Simple and effective
strategies for achieving diverse and competitive structural designs,” Extreme Mechanics Letters,
vol. 30, 100481, 2019.
 Z. L. Zhao, S. Zhou, X. Q. Feng and Y. M. Xie, “On the internal architecture of emergent plants,”
Journal of the Mechanics and Physics of Solids,vol. 119, pp. 224–239, 2018.
 J. Burry, P. Felicetti, J. Tang, M. Burry and Y. M. Xie, “Dynamical structural modelling: a
collaborative design exploration,” International Journal of Architectural Computing, vol. 3, pp.
 X. Huang, Y. M. Xie and M. C. Burry, “A new algorithm for bi-directional evolutionary structural
optimization,” International Journal of the Japan Society of Mechanical Engineers, vol. C49, pp.
 P. F. Yuan, H. Chai and Y. M. Xie, “Towards a structural performance-based architectural design
in digital age,” Architectural Journal, vol. 11, pp. 1-8, 2017.
S. Bialkowski, “Structural optimization methods as a new tool for architects’, Design Tools
Explorations, vol.2, eCAADe, pp. 255-264, 2016