Sensors and Workflow Evolutions

Sensors and Workflow Evolutions: Developing A

Framework for Instant Robotic Toolpath Revision

Alexandre Dubor1, Guillem Camprodom1, Gabriel Bello Diaz2, Dagmar Reinhardt3, Kate Dunn4 and Rob Saunders3
1 Institute for Advanced Architecture of Catalonia (IAAC)
2 Make It Locally
3 The University of Sydney
4 University of New South Wales
Fig. 1. Common CAD + CAM workflow

This paper examines the potential for creative practitioners to adopt robotic fabrication processes augmented with the introduction of sensors. Typically, the outcomes of a fabrication process are predetermined, however, with the introduction of sensors, design and fabrication process may be interrupted by real-time feedback. In such a system, design roles and authorship become secondary to the process of manipulating data, such that new rules of design can be introduced and developed in response to materials.

Fig. 2. Parametric workflow: using parametric design for material exploration

Hardware and software such as Arduino, Grasshopper3D, Rhinoceros3D and Processing have opened up new strategies of hacking, coding and robotic manipulation that can be embedded in robotic fabrication processes. The addition of sensors provides feedback about material location and characteristics, work environment and co-workers, so as to support architectural dialogue. This paper proposes a framework for designing new protocols for human interaction and machine response in robotic fabrication systems.

Fig. 3. 3D printing process informed by sensors (Pylos Project, IAAC, 2014)

Progress in robotic fabrication and manufacturing has accelerated in recent years through research in industry, practice, construction and manufacturing (Gramazio and Kohler, 2014). Robotic fabrication labs are now embedded in professional practices, educational institutions and research centers across architecture, art and design.

While robotic fabrication has extended previous automation processes of the automotive industry towards complex and singular fabrication solutions, the challenge is now to expand the negotiation of robotic processes—to influence toolpath options and define new material processes—in short to introduce a form of design thinking (Moggridge, 2007) for robotics with the goal of enhancing creativity and the evolution of design processes, models, and techniques.

Fig. 4. Iterative workflow: embedding sensor feedback in the parametric design

Robotic fabrication processes enable designers and architects to explore the boundaries between digital and material worlds. Beyond optimization criteria or parametric design, new design strategies such as generative design and collaborative design are enabling new ways of approaching material exploration through robotics.

Open source software and hardware enable new forms of design, yet these new tools also demand design frameworks dealing with robots, data, sensor technologies and material contingencies.

Fig. 5. Behavioral Workflow: embedding response to sensor feedback in fabrication logic

Public interest in digital fabrication and the rising availability of 3D printers has allowed an increasing number of non-specialists to understand and adapt the logic and mechanisms behind the materialization process. It is now becoming common for users to change parameters of a digital fabrication process, e.g., feed-rates and the nozzle temperatures, to adapt it to their specific requirements.

Fig. 6. Sense-it 6 axis workshop

In addition, the spread of open source hardware and software has empowered hobbyists, artists and designers to build their own machines, permitting the rise to new types of machines and fabrication processes. In architecture, industrial robots have proven to be robust and flexible research platform, allowing the precise placement of many types of tool within a large working envelope, allowing the designer to focus on the design of novel end-effector and processes.

Fig. 7. l’Artisan électronique (© UNFOLD, Belgium, 2010)

The division between design and fabrication process is slowly disappearing in favor of a continuous form of design, which includes fabrication as an essential element. While providing a great framework for fast iteration and exploration, linear approaches reach their limit when fabrication becomes more complicated, requiring lengthy iterations.

In addition, complex fabrication processes that use non-static materials, e.g., clay or polymer, require more precise and sensor feedback to enable tracking, fine-tuning and synchronization between material, machine and design. Sensors thus enable real-time feedback loops that have the potential to radically change the design process.

Fig. 8. Digital Craftsman Workflow: Combining digital and manual fabrication

The act of giving a machine freedom to assist the creative process leads to unexpected and useful information both from the machine and material perspective. By coupling Human-Machine Interface with robotic fabrication, sensor feedback and digital computation, new possibilities for creative collaboration are appearing. Collaboration between robots and human can enhance creativity and innovation by supporting designer and researcher while exploring complex material system.

Fig. 9. Collaborative Workflow: Coupling human-machine interface with robotic fabrication, sensor feedback and digital computation

Such material exploration through robotic fabrication can gain precision and in depth information from sensor analysis of the material, the context and the user’s movements. The advantages associated with an open-source framework and low cost sensors may permit widespread adoption of this approach and enhance new collaboration between researchers and designers.

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