Category: Weekly Progress Update

Generating architectural shapes and stepping out of my comfort zone – final thoughts about P3

For the final stage of the first part of this project, I have experimented further with combining different meshes and settings for the agents in Culebra to see what architectural shapes can be generated based on different criteria. I produced a series of 25 architectural shapes/pavillions, intuitively testing different settings to generate different architectural elements. After generating the pavillions, I zoomed in on them to identify different architectural elements/typologies that had emerged based on different settings.

My usual process when working with architectural projects is quite rational and controlled. Trying to let go of my own expectations for what the end result will be has been a challenge for me during this project. During my presentation, I got the comment that I from here on should try to take a step back to a more rational, controlled process and set of rules for the Culebra agents. Getting that comment was a big victory for me, as proof that I managed to step outside of my regulated and boxy comfort zone and just try something new based on intuition. I am very much looking forward to the next part of the project, since I hopefully will get a chance to keep working on finding the balance between controlled/rational/result-oriented and intuitive design processes.

iv. movement simulation and data management

Moving on from the last pin-up I needed a better management strategy for the site data. When the robot reads and responds to the site it needs to be at a scale that the data is useable and realistic for the architectural design to be implemented. Providing a grid system allowed a reading of the entire terrain in greater detail where each grid tile can be blown up and analysed. Consideration was also taken for the dimensions of a manageable testing area for repeated demonstrations and data collection. Below are two possible methods of grid reading of the site. The maps were sampled at 1:500 scale with the second method of grid division.

The robot has a narrow range of testing limited to its line and ultrasonic sensors. This provides a linear path of testing at 1cm intervals on the sample map which would be every 50metres in real life. This gives a dimension and scale to any output that will be collected. In the simulation drawings, the robot is to respond to the changes in height at any level changes, changes at the highest and lowest areas. The output is a full 360 rotation of the robot leaving circles as the response. The robot is allowed to respond to its generated data again and draw diagonal lines at a 45 degree angle at every circle. This then gives a criss cross of linear data that the building system of precast members could be assembled upon.

More lines and circles!

Since the last post, I back tracked a little bit to refine and rationalise the ‘loop’ path. By analysing the steepness of this region in more detail, ridges in the rock are highlighted. I then traced these ridges and extended them to meet the next one, which formed a boundary. I took the inner region of these lines, and gave a fillet at the intersections. This loop is now a series of straight segments and arcs.

Rationalising the path | Plan of Dödviken

A benefit of building along ridges along the site is that it lowers the highest point along the route. This means that the path, which is at the average height of all the points it crosses, is lower. The bridges are a more reasonable height above the water, and the tunnels are at a more reasonable depth within the ground.

I would like to begin to analyse segments along the route for their materiality and geometry, both along the path and perpendicular to it. This can begin to form rules and inform the program of the camp.

Finally, this model shows a segment along the route where the path cuts through the rock as a tunnel, crosses over the water as a bridge, and continues over the ground as a path.

1:200 Sectional Model of Path

iii. recalibration…error!*2

The robot allows for direct feedback for the design strategy proposal. In oder to fully apply this method of working I formulated a strategy for the summer camp as an initial system of production, construction and form to allow for freedom in testing.

I took the soviet architectural town planning in 1930 by E. May as precedent. The linear markings on the site appears to respond to the context yet also offer an abstract notation of the program of development. The summer camp proposal for Malmon will be about setting up a grid that will be the groundwork for precast members that can easily be assembled and disassembled. Concepts of sustainability and impermanence are suggested.

To obtain an output from the robot I 3D printed a set of arms/ pen holders to obtain a line drawing from the site analysis. While the robot scans the site, It would produce a line drawing as a data output. The implementation was dictated by the robots sensors, size and my coding capabilities. I did not achieve an outcome that could be presented or represented the idea. For the final task in this project I will work towards focusing on what data I want as an output and a much simpler application of the robots abilities.

Site and topography

This week, I have been working on finetuning the Culebra swarms while also experimenting more with generating meshes in Grasshopper using different raster images of the topography. 

After creating a simple script to detect the most dense areas from one of the swarm iterations from last time, I have chosen the southern tip of the island, Draget, to be my site. 

The work done this week sparked my interest in looking even more in detail in the different possible outcomes of using image samplers on different topographical data sources; more specifically, I am going to investigate the different outcomes between the heightmap raster image versus the ortho photo from Lantmäteriet. This investigation, in combination with seeing in how the swarming agents from Culebra can interact with both each other and the different topography meshes, is what I am planning on looking at during the coming weeks.

ii. big data and nomadic robotics.

Studio 9_Project 3_Task 2: Occupations and Interventions.

To occupy the site I began by collecting and analysing site data for Malmön. The program QGIS for editing and analysing geospatial information was used to extract the vector information; topography, population and marine geology. A colour png map provided the basis for extracting the 3D terrain data using a python script and into Rhino, with initial topography analysis through flow diagrams in grasshopper. A photographic study was also carried out and compiled into a booklet.

The intervention aspect was based heavily on ABM research – agent based models. An agent is aware of its surroundings and its abilities. When acting in a collective manner they exhibit swarm intelligence, the collective behaviour of decentralised self-organised systems. This means each member autonomously offers its abilities in order to study an overall system. The members, or agents, self-coordinates without a leader and cooperate in solidarity resulting in a self-healing system. This allows members to be added or removed dynamically as the agents will recalibrate in a constant feedback loop.

‘Boids’ by Craig Reynolds was the grounds for my research into swarms and flocking behaviours for computer simulations. His theory is a basic flocking model consisting of three steering behaviours; separation, alignment and cohesion. Ant colonies that organise using pheromone and visibility factors were also part of the initial studies.

I would like to base project 3 on the collection of site data using agents and subsequently allowing the agents to alter the collected data in order to intervene and implement the summer camp design on Malmön. To engage with this theory in the material dimension, I decided give form to the agent as a mini Arduino robot name Mö. This allows for real-time feedback with the tests I run for the agent simulation on site. Giving robotics agent behaviours has its own research and theory basis. Although Craig Reynolds theory of Boids is a great foundation, I also studied vehicle behaviour and coding in ‘Vehicles: Experiments in Synthetic Psychology’ by Valentino Braitenberg. Processing and Arduino will be the main programming softwares, with C and Java as scripting languages. The Nature of Code on youtube and Github, as well as Studio 09’s own processing tutorials have been great learning platforms for this.

i. research.

Studio 9_Project 3_Task 1 : Human reading.

The 9 projects below were collected as precedents for project 3.

These plans and sections are a representation of two strings of thought; i. an exploration of form and approaches to setting; ii. city making and sequential building. The first set of projects play with ideas of control, vistas and the act of an icon in the landscape. They tackle form and building materials in an experimental manner using the environment and new technology as key tools. A simple question of building up or down and along the terrain is also brought to question. The second string of thought is concerned with city making and sequential building with studies of the layout of the city of Pompeii, the Acropolis of Athens and futuristic plug-in cities.

Precedents, Posterization in Python and Participatory Processes

Without anything specific in mind, I started out by researching the camp typology in a broad sense, collecting examples spanning from military camps to inca ruins. The collection of precedents is therefore quite diverse, not (yet, at least) neatly categorized by any specific parameters. However, a few different patterns emerge, such as strict, square grid compositions or more rounded landscape excavations.

The terraced landscapes in Moray and Dalhalla in combination with Pablo’s Python script to modify the heightmap image file inspired me to experiment with programming a script that modifies the heightmap to create a posterized, lower resolution version of the image that in turn could generate a terraced landscape in Rhino. I am not yet sure whether this type of terraforming is what I want to work with moving forward in the project, but at least I had fun writing my first few lines of code.

At present, my area of interest for the camp project is related to participatory and/or emergent design, where the participants of the camp are the ones designing/building/influencing the camp in some way. Instead of ending up with a finished ”project” showing a final end result for what the camp will look like, it might be interesting to work towards a more speculative, ”simulated” result, showing a possible outcome of a process, perhaps happening over a longer period of time. An idea on how take this vague and overly ambitious idea forward is to analyze settlements that have emerged organically without architects to identify the rules and patterns of the configurations. I am also planning on looking more at the specifics of the site, as well as gathering more references on participatory and emergent design processes.