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As part of TU Delft Rhizome 2.0 and Moonshot projects, focusing on the development of extraterrestrial habitats in lava tubes, the robotic mapping of an analogue lava tube in Sicily has been studied with the future goal of assessing its suitability for building construction. The main objective of the research was to survey a lava tube and acquire a novel dataset for future research, while also analyzing the collected data to evaluate possible future lava tube exploration scenarios for the Moon and Mars. This paper presents the robotic mapping conducted in Grotta di Monte Intraleo, detailing the implementation and outlining challenges and insights, leading to the new dataset. Various mapping and data collection methods, including robotic mapping using LiDAR, was explored. The overall strategy relies on multi-technique scanning to enhance redundancy and ensure comprehensive data acquisition, that is providing a robust foundation for future robotic exploration and habitat planning.
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As part of TU Delft Rhizome 2.0 and Moonshot projects, focusing on the development of extraterrestrial habitats in lava tubes, the robotic mapping of an analogue lava tube in Sicily has been studied with the future goal of assessing its suitability for building construction. The main objective of the research was to survey a lava tube and acquire a novel dataset for future research, while also analyzing the collected data to evaluate possible future lava tube exploration scenarios for the Moon and Mars. This paper presents the robotic mapping conducted in Grotta di Monte Intraleo, detailing the implementation and outlining challenges and insights, leading to the new dataset. Various mapping and data collection methods, including robotic mapping using LiDAR, was explored. The overall strategy relies on multi-technique scanning to enhance redundancy and ensure comprehensive data acquisition, that is providing a robust foundation for future robotic exploration and habitat planning.
Constructing Martian habitats presents significant challenges due to the harsh environmental conditions and limited resources available. In the presented study, a robotic assembly method has been developed that incorporates K-means clustering for task allocation and topological interlocking. The topological interlocking of Voronoi-based components provides an internally force-locked system, which facilitates both the robotic assembly process and the structural stability of the habitat. The clustering is leveraged for production planning objectives, including resource allocation and scheduling operations for assembling components. This method addresses assembly challenges of nonuniform components and facilitates the stacking of prefabricated 3D-printed Voronoi-based components using mobile robots. Experimental tests show that the proposed approach is practical and scalable, offering a feasible solution for autonomous Martian habitat construction. It contributes to laying the groundwork for sustainable autonomous construction systems.
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Constructing Martian habitats presents significant challenges due to the harsh environmental conditions and limited resources available. In the presented study, a robotic assembly method has been developed that incorporates K-means clustering for task allocation and topological interlocking. The topological interlocking of Voronoi-based components provides an internally force-locked system, which facilitates both the robotic assembly process and the structural stability of the habitat. The clustering is leveraged for production planning objectives, including resource allocation and scheduling operations for assembling components. This method addresses assembly challenges of nonuniform components and facilitates the stacking of prefabricated 3D-printed Voronoi-based components using mobile robots. Experimental tests show that the proposed approach is practical and scalable, offering a feasible solution for autonomous Martian habitat construction. It contributes to laying the groundwork for sustainable autonomous construction systems.
When designing and constructing habitats on Mars, one of the main challenges is the extreme environment, which lacks a breathable atmosphere and atmospheric pressure, and is characterized by extreme temperature fluctuations and high radiation levels. The habitat is situated within a lava tube, providing natural shielding from radiation, micrometeoroids, and extreme temperature fluctuations. This challenge is addressed in TU Delft’s Rhizome 2.0 project by integrating a Life Support System (LSS) into the envelope of a Martian habitat to maintain the necessary environmental conditions for human survival. The research explores the integration of the LSS into the approximately 1.5-m-thick building envelope that is constructed from prefabricated 3D-printed Voronoi-based components that interlock and are assembled on-site by a swarm of rovers and human assistance where needed. The integration is implemented by structurally analyzing the envelope to generate a point cloud of stress data. Based on the stress concentrations and LSS conduit path lengths, a single objective optimizer determines the shortest routes for the LSS conduits while avoiding high stress concentrations. This results in a structurally optimized building envelope with strategically incorporated branching negative spaces that accommodate the LSS infrastructure.
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When designing and constructing habitats on Mars, one of the main challenges is the extreme environment, which lacks a breathable atmosphere and atmospheric pressure, and is characterized by extreme temperature fluctuations and high radiation levels. The habitat is situated within a lava tube, providing natural shielding from radiation, micrometeoroids, and extreme temperature fluctuations. This challenge is addressed in TU Delft’s Rhizome 2.0 project by integrating a Life Support System (LSS) into the envelope of a Martian habitat to maintain the necessary environmental conditions for human survival. The research explores the integration of the LSS into the approximately 1.5-m-thick building envelope that is constructed from prefabricated 3D-printed Voronoi-based components that interlock and are assembled on-site by a swarm of rovers and human assistance where needed. The integration is implemented by structurally analyzing the envelope to generate a point cloud of stress data. Based on the stress concentrations and LSS conduit path lengths, a single objective optimizer determines the shortest routes for the LSS conduits while avoiding high stress concentrations. This results in a structurally optimized building envelope with strategically incorporated branching negative spaces that accommodate the LSS infrastructure.
The European Space Agency (ESA) funded project, Rhizome, implemented at Technical University (TU) Delft, Netherlands in collaboration with industrial partner, Vertico, focuses on the development of extraterrestrial habitats constructed from robotically printed components that are assembled into larger structures using a swarm of rovers. The habitat has an integrated greenhouse that relies among others on robotic planting. The developed Computer Vision (CV)- and Human–Robot Interaction (HRI)-supported approach implemented in collaboration with the University of Sydney (U Sydney) and the University of New South Wales (UNSW), Australia, facilitates the planting. It aims at minimizing use of human resources. Furthermore, it contributes to sustainability by (a) increasing efficiency, with robots planting seedlings faster and with greater precision than humans and by (b) improving resource utilization, with robots accurately planting seedlings at optimal spacing and depth to minimize use of water, nutrients, etc. The developed robotic approach relies on a mobile robotic system equipped with an anthropomorphic robotic hand based on soft-robotics technology, able to interact with the surrounding environment, objects, and humans. For planting, the robotic hand uses 2 Degrees of Freedom (DOF) to open and close and a camera mounted to the side of the robotic arm to capture the working area. By detecting the position and directional vector of the individual seedlings, the robotic hand is automatically positioned and suitably aligned for the seedling pickup. While a predefined automated pick-and-place code determines the planting positions, the human assists the robotic hand with gently grabbing and releasing the seedling. This approach aims to adapt robots to human interactions over time by improving their performance and responsiveness using reinforcement or imitation learning in due time. The overall goal is to advance sustainable development of habitats with integrated greenhouses through robotic technology transfer from on- to off-Earth applications and vice versa.
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The European Space Agency (ESA) funded project, Rhizome, implemented at Technical University (TU) Delft, Netherlands in collaboration with industrial partner, Vertico, focuses on the development of extraterrestrial habitats constructed from robotically printed components that are assembled into larger structures using a swarm of rovers. The habitat has an integrated greenhouse that relies among others on robotic planting. The developed Computer Vision (CV)- and Human–Robot Interaction (HRI)-supported approach implemented in collaboration with the University of Sydney (U Sydney) and the University of New South Wales (UNSW), Australia, facilitates the planting. It aims at minimizing use of human resources. Furthermore, it contributes to sustainability by (a) increasing efficiency, with robots planting seedlings faster and with greater precision than humans and by (b) improving resource utilization, with robots accurately planting seedlings at optimal spacing and depth to minimize use of water, nutrients, etc. The developed robotic approach relies on a mobile robotic system equipped with an anthropomorphic robotic hand based on soft-robotics technology, able to interact with the surrounding environment, objects, and humans. For planting, the robotic hand uses 2 Degrees of Freedom (DOF) to open and close and a camera mounted to the side of the robotic arm to capture the working area. By detecting the position and directional vector of the individual seedlings, the robotic hand is automatically positioned and suitably aligned for the seedling pickup. While a predefined automated pick-and-place code determines the planting positions, the human assists the robotic hand with gently grabbing and releasing the seedling. This approach aims to adapt robots to human interactions over time by improving their performance and responsiveness using reinforcement or imitation learning in due time. The overall goal is to advance sustainable development of habitats with integrated greenhouses through robotic technology transfer from on- to off-Earth applications and vice versa.
Rhizome 1.0 and 2.0 are European Space Agency (ESA) co-funded projects that have been implemented with a team from the Architecture, Mechanical Engineering, and Aerospace Engineering Faculties, TU Delft, and various industrial partners. The focus is on the development of a Martian habitat using 3D-printed components and in situ resource utilization. This paper presents a new multi-modal method developed for the collaborative assembly of building components with the support of Computer Vision (CV) and Human-Robot Interaction (HRI) using compliant robotic collaborative manipulators. The building components are Voronoi-based and are fabricated using Design-to-Robotic-Production and -Assembly (D2RP&A). During the collaborative assembly, the robot uses CV to detect the fabricated component and generate autonomous actions to perform the pick-and-place movement. Between the autonomous robot actions, HRI is used by the human to physically guide the robot when grasping and positioning. To evaluate the proposed method, lab experiments were conducted using robotically milled mock-up components from Styrofoam, which were assembled with a collaborative robotic arm. The results indicate that robots can assist humans during the assembly process to implement tasks that are beyond their physical abilities, while robots benefit from human cognitive capabilities during more complex actions.
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Rhizome 1.0 and 2.0 are European Space Agency (ESA) co-funded projects that have been implemented with a team from the Architecture, Mechanical Engineering, and Aerospace Engineering Faculties, TU Delft, and various industrial partners. The focus is on the development of a Martian habitat using 3D-printed components and in situ resource utilization. This paper presents a new multi-modal method developed for the collaborative assembly of building components with the support of Computer Vision (CV) and Human-Robot Interaction (HRI) using compliant robotic collaborative manipulators. The building components are Voronoi-based and are fabricated using Design-to-Robotic-Production and -Assembly (D2RP&A). During the collaborative assembly, the robot uses CV to detect the fabricated component and generate autonomous actions to perform the pick-and-place movement. Between the autonomous robot actions, HRI is used by the human to physically guide the robot when grasping and positioning. To evaluate the proposed method, lab experiments were conducted using robotically milled mock-up components from Styrofoam, which were assembled with a collaborative robotic arm. The results indicate that robots can assist humans during the assembly process to implement tasks that are beyond their physical abilities, while robots benefit from human cognitive capabilities during more complex actions.
Constructing a Martian habitat presents significant challenges due to extreme temperature variations and a low-density and -pressure atmosphere. To address these challenges a habitat constructed from prefabricated, interlocking Voronoi-based components that are assembled by human-robot collaboration has been explored in the Rhizome projects at TU Delft. In this paper, we propose a combined robot motion planning and learning method that can optimize human involvement in assembly tasks in on-site construction. The proposed hybrid approach exploits motion planning to create motion trajectories for aspects of the task where robot autonomy is capable of solving the problem on its own using sensors and intelligence. When the task becomes too difficult for existing planning capabilities, the human can step in and teach motion trajectories via kinaesthetic demonstration using Dynamic Movement Primitives (DMPs). The trajectories are then executed on the low level by an impedance controller to handle the physical interaction with the environment during the assembly. The decision-making process is managed by a behavior tree.
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Constructing a Martian habitat presents significant challenges due to extreme temperature variations and a low-density and -pressure atmosphere. To address these challenges a habitat constructed from prefabricated, interlocking Voronoi-based components that are assembled by human-robot collaboration has been explored in the Rhizome projects at TU Delft. In this paper, we propose a combined robot motion planning and learning method that can optimize human involvement in assembly tasks in on-site construction. The proposed hybrid approach exploits motion planning to create motion trajectories for aspects of the task where robot autonomy is capable of solving the problem on its own using sensors and intelligence. When the task becomes too difficult for existing planning capabilities, the human can step in and teach motion trajectories via kinaesthetic demonstration using Dynamic Movement Primitives (DMPs). The trajectories are then executed on the low level by an impedance controller to handle the physical interaction with the environment during the assembly. The decision-making process is managed by a behavior tree.
Building pop-up habitats in extreme weather conditions such as deserts requires preliminary contextual, i.e., site studies. Since the site’s condition is constantly changing due to sand relocation induced by wind, a rapid mapping solution is proposed. This is implemented by generating a 3D mesh model of the site with the help of a visual workflow and advanced computational design methods to implement in-situ 3D printing of habitats. This paper presents an integrated approach utilizing Computer Vision (CV), Deep Learning (DL), and generative design tools like Grasshopper. By harnessing the potential of Convolutional Neural Networks (CNNs), a robust framework is developed to recognize complex desert terrain features, independent of solar orientation and camera positioning. The methodology employs a state-of-the-art CNN customized for detecting features in desert settings. This is further enhanced by using Grasshopper to systematically generate a diverse dataset that enriches the model’s learning process. The resulting model efficiently extracts precise 3D meshes from 2D images, optimizing site mapping and integrating habitat printing workflows. This automated approach offers an effective solution for habitat construction in challenging environments, showcasing real-time processing.
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Building pop-up habitats in extreme weather conditions such as deserts requires preliminary contextual, i.e., site studies. Since the site’s condition is constantly changing due to sand relocation induced by wind, a rapid mapping solution is proposed. This is implemented by generating a 3D mesh model of the site with the help of a visual workflow and advanced computational design methods to implement in-situ 3D printing of habitats. This paper presents an integrated approach utilizing Computer Vision (CV), Deep Learning (DL), and generative design tools like Grasshopper. By harnessing the potential of Convolutional Neural Networks (CNNs), a robust framework is developed to recognize complex desert terrain features, independent of solar orientation and camera positioning. The methodology employs a state-of-the-art CNN customized for detecting features in desert settings. This is further enhanced by using Grasshopper to systematically generate a diverse dataset that enriches the model’s learning process. The resulting model efficiently extracts precise 3D meshes from 2D images, optimizing site mapping and integrating habitat printing workflows. This automated approach offers an effective solution for habitat construction in challenging environments, showcasing real-time processing.
Human-Building Interaction (HBI) relies on sensor-actuator networks that are increasingly supported by Artificial Intelligence (AI). This paper presents a novel AI-supported Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) approach for reconfigurable furniture. It involves a multidisciplinary approach that relies on the integration of various domains such as architecture, robotics, computer, and material science. It contributes to the advancement of HBI by employing spatial reconfiguration relying on AI and lightweight material design, which is of relevance, particularly when the furniture consists of non-identical but similar components that are re−/ configured in a variety of possible combinations.
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Human-Building Interaction (HBI) relies on sensor-actuator networks that are increasingly supported by Artificial Intelligence (AI). This paper presents a novel AI-supported Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) approach for reconfigurable furniture. It involves a multidisciplinary approach that relies on the integration of various domains such as architecture, robotics, computer, and material science. It contributes to the advancement of HBI by employing spatial reconfiguration relying on AI and lightweight material design, which is of relevance, particularly when the furniture consists of non-identical but similar components that are re−/ configured in a variety of possible combinations.
In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several metres thick. In a feasibility study, funded by the European Space Agency, Technical University Delft (TUD aka TU Delft) explored the possibility of building in empty lava tubes to create rhizomatic subsurface habitats. With this approach natural protection from radiation is achieved as well as thermal insulation because the temperature is more stable underground. It involves a swarm of autonomous mobile robots that survey the areas and mine for materials such as regolith in order to create cement-based concrete reproducible on Mars through in-situ resource utilisation (ISRU). The concrete is 3D printed by means of additive Design-to-Robotic-Production (D2RP) methods developed at TUD for on-Earth applications with the 3D printing system of industrial partner, Vertico. The printed components are assembled using a Human--Robot Interaction (HRI) supported approach. The 3D printed and HRI-supported assembled structures are structurally optimised porous material systems with increased insulation properties. In order to regulate the indoor pressurised environment a Life Support System (LSS) is integrated, which in this study is only conceptually developed. The habitat and the D2RP production system are powered by an automated kite power system and solar panels developed at TUD. The long-term goal is to develop an autarkic, automated and HRI-supported D2RP system for building autarkic habitats from locally obtained materials.
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In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several metres thick. In a feasibility study, funded by the European Space Agency, Technical University Delft (TUD aka TU Delft) explored the possibility of building in empty lava tubes to create rhizomatic subsurface habitats. With this approach natural protection from radiation is achieved as well as thermal insulation because the temperature is more stable underground. It involves a swarm of autonomous mobile robots that survey the areas and mine for materials such as regolith in order to create cement-based concrete reproducible on Mars through in-situ resource utilisation (ISRU). The concrete is 3D printed by means of additive Design-to-Robotic-Production (D2RP) methods developed at TUD for on-Earth applications with the 3D printing system of industrial partner, Vertico. The printed components are assembled using a Human--Robot Interaction (HRI) supported approach. The 3D printed and HRI-supported assembled structures are structurally optimised porous material systems with increased insulation properties. In order to regulate the indoor pressurised environment a Life Support System (LSS) is integrated, which in this study is only conceptually developed. The habitat and the D2RP production system are powered by an automated kite power system and solar panels developed at TUD. The long-term goal is to develop an autarkic, automated and HRI-supported D2RP system for building autarkic habitats from locally obtained materials.
Real-world applications of Artificial Intelligence (AI) in architecture have been explored more recently at Technical University (TU) Delft by integrating AI in Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) methods. These embed robotics into building processes and buildings by linking computational design with robotic construction and/ or operation of building components and buildings. This paper presents two case studies in which AI-supported D2RA is implemented in a multidisciplinary approach that requires the integration of research domains such as architecture, robotics, computer and material science.
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Real-world applications of Artificial Intelligence (AI) in architecture have been explored more recently at Technical University (TU) Delft by integrating AI in Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) methods. These embed robotics into building processes and buildings by linking computational design with robotic construction and/ or operation of building components and buildings. This paper presents two case studies in which AI-supported D2RA is implemented in a multidisciplinary approach that requires the integration of research domains such as architecture, robotics, computer and material science.
This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.
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This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.
This chapter presents a review of cementless materials for 3D printing, with a specific emphasis on the utilization of volcanic ash in the context of a case study for off-Earth construction. As a highly promising alternative to traditional concrete, selected binders are investigated in relation to volcanic ash for the creation of an alternative concrete. These offer a multitude of compelling advantages, including exceptional sustainability, local availability, and minimal energy use. By opting for volcanic ash-based materials, a significant reduction in resource consumption and pollution can be achieved. The review concludes with a set of considerations aimed at addressing various critical aspects related to volcanic ash-based materials. These considerations encompass vital areas such as binder selection, printability, structural behavior, production optimization, in-situ resource utilization, and sustainability. The goal is to establish a solid foundation for the widespread application of cementless concrete by understanding materials, particularly in the context of utilizing volcanic ash, and thereby fostering a paradigm shift toward more environmentally friendly and resource-efficient construction practices.
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This chapter presents a review of cementless materials for 3D printing, with a specific emphasis on the utilization of volcanic ash in the context of a case study for off-Earth construction. As a highly promising alternative to traditional concrete, selected binders are investigated in relation to volcanic ash for the creation of an alternative concrete. These offer a multitude of compelling advantages, including exceptional sustainability, local availability, and minimal energy use. By opting for volcanic ash-based materials, a significant reduction in resource consumption and pollution can be achieved. The review concludes with a set of considerations aimed at addressing various critical aspects related to volcanic ash-based materials. These considerations encompass vital areas such as binder selection, printability, structural behavior, production optimization, in-situ resource utilization, and sustainability. The goal is to establish a solid foundation for the widespread application of cementless concrete by understanding materials, particularly in the context of utilizing volcanic ash, and thereby fostering a paradigm shift toward more environmentally friendly and resource-efficient construction practices.
In the original version of the book, on page xi, one of the authors listed for Chapter 2 is “R. Schnmehl”, which should be “R. Schmehl”. On page 21, the same correction needs to be made twice, in the listed authors at the top of the page and also in the footnotes. “Schnmehl” should become “Schmehl” in both the cases. This has now been rectified and the author’s name has been corrected. The correction to this book have been updated with the changes.
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In the original version of the book, on page xi, one of the authors listed for Chapter 2 is “R. Schnmehl”, which should be “R. Schmehl”. On page 21, the same correction needs to be made twice, in the listed authors at the top of the page and also in the footnotes. “Schnmehl” should become “Schmehl” in both the cases. This has now been rectified and the author’s name has been corrected. The correction to this book have been updated with the changes.
This paper revisits existing pop-up typologies in architecture to identify opportunities for new shelter models to address current housing demands and future habitation requirements on Mars. It presents advancements in design to production methodologies based on computational and robotic techniques to meet current requirements and affordances while integrating sustainable and adaptive functionalities. The main goal is to advance pop-up architecture by developing methods and technologies for rapidly deployable on- and off-Earth habitats while addressing challenges of carbon-free architecture by means of 3D printing. By reviewing state-of-the-art in-situ vs. prefab 3D printing approaches with a particular focus on Human-Robot Interaction (HRI) supported Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) methods developed at TU Delft material, process, and energy efficiency using locally sourced materials is achieved.
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This paper revisits existing pop-up typologies in architecture to identify opportunities for new shelter models to address current housing demands and future habitation requirements on Mars. It presents advancements in design to production methodologies based on computational and robotic techniques to meet current requirements and affordances while integrating sustainable and adaptive functionalities. The main goal is to advance pop-up architecture by developing methods and technologies for rapidly deployable on- and off-Earth habitats while addressing challenges of carbon-free architecture by means of 3D printing. By reviewing state-of-the-art in-situ vs. prefab 3D printing approaches with a particular focus on Human-Robot Interaction (HRI) supported Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) methods developed at TU Delft material, process, and energy efficiency using locally sourced materials is achieved.
The construction sector accounts for about 40% of material-, energy- and process-related carbon dioxide (CO2) emissions, which can be reduced by introducing data-driven Circular Economy (CE) approaches. For instance, Design-to-Robotic-Production (D2RP) methods developed in the Robotic building lab, at Technical University (TU) Delft are embedding data-driven systems into building processes. Their potential to contribute to sustainability through increased material-, process-, and energy-efficiency has been explored in several case studies that are presented in this paper. The assumption is that by using these methods and reclaimed wood to minimize demand for new resources and reduce deforestation along the way, CO2 emissions can be considerably reduced.
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The construction sector accounts for about 40% of material-, energy- and process-related carbon dioxide (CO2) emissions, which can be reduced by introducing data-driven Circular Economy (CE) approaches. For instance, Design-to-Robotic-Production (D2RP) methods developed in the Robotic building lab, at Technical University (TU) Delft are embedding data-driven systems into building processes. Their potential to contribute to sustainability through increased material-, process-, and energy-efficiency has been explored in several case studies that are presented in this paper. The assumption is that by using these methods and reclaimed wood to minimize demand for new resources and reduce deforestation along the way, CO2 emissions can be considerably reduced.
Ambient intelligence (AmI) relying on electronic devices employing information and communication technology (ICT) and artificial intelligence (AI) embedded in the network connecting these devices tends today to be insufficiently used. This deficiency implies that spaces are uncomfortable and considerable energy dissipates due to distribution losses, excessive or unnecessary climate control of little- and unoccupied spaces, etc. Building operations are responsible for ±27% of annual carbon dioxide (CO
2) emissions, and infrastructure materials and construction are responsible for an additional ±13% annually; both need to be addressed integratively to meet sustainability goals.
1,2 This paper addresses this in three AI-supported AmI test simulations of applications focusing on illumination and ventilation systems embedded in the built environment.
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Ambient intelligence (AmI) relying on electronic devices employing information and communication technology (ICT) and artificial intelligence (AI) embedded in the network connecting these devices tends today to be insufficiently used. This deficiency implies that spaces are uncomfortable and considerable energy dissipates due to distribution losses, excessive or unnecessary climate control of little- and unoccupied spaces, etc. Building operations are responsible for ±27% of annual carbon dioxide (CO
2) emissions, and infrastructure materials and construction are responsible for an additional ±13% annually; both need to be addressed integratively to meet sustainability goals.
1,2 This paper addresses this in three AI-supported AmI test simulations of applications focusing on illumination and ventilation systems embedded in the built environment.
With current advancements in Cyber-physical Systems (CpS), data-driven design to both production and operation processes has been increasingly incorporating aspects of robotics and Artificial Intelligence (AI). These aspects are the focus of architectural exploration implemented in the Robotic Building lab at Technical University (TU) Delft using Design-to-Robotic-Production and -Operation (D2RP&O) methods. In the presented project implemented in collaboration with the Landscape Architecture and Informatics departments from TU Delft and the University of Fribourg, respectively, new habitats are developed for various animal and plant species by introducing small-scale interventions in residual space. The intention for these inserts is to support biodiversity by engaging humans in interaction with them and each other. In this context, the inserts are not only produced by computational and robotic means, but they also contain sensor–actuator mechanisms that allow humans to interact with them by establishing bio-cyber-physical feedback loops. The aim is to identify the challenges and potential of such systems to improve spatial experience, increase social interaction, as well as support biodiversity, in urban environments.
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With current advancements in Cyber-physical Systems (CpS), data-driven design to both production and operation processes has been increasingly incorporating aspects of robotics and Artificial Intelligence (AI). These aspects are the focus of architectural exploration implemented in the Robotic Building lab at Technical University (TU) Delft using Design-to-Robotic-Production and -Operation (D2RP&O) methods. In the presented project implemented in collaboration with the Landscape Architecture and Informatics departments from TU Delft and the University of Fribourg, respectively, new habitats are developed for various animal and plant species by introducing small-scale interventions in residual space. The intention for these inserts is to support biodiversity by engaging humans in interaction with them and each other. In this context, the inserts are not only produced by computational and robotic means, but they also contain sensor–actuator mechanisms that allow humans to interact with them by establishing bio-cyber-physical feedback loops. The aim is to identify the challenges and potential of such systems to improve spatial experience, increase social interaction, as well as support biodiversity, in urban environments.
In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several meters thick. Technical University Delft (TUD) proposes to excavate into the ground to create subsurface habitats. By excavating, not only can natural protection from radiation be achieved but also thermal insulation, as the temperature is more stable underground. At the same time, valuable resources can be excavated via in-situ resource utilization (ISRU). In this process, a swarm of autonomous mobile robots excavate the ground in a downwards sloping spiral movement. The excavated regolith will be mixed with cement, which can be produced on Mars through ISRU, in order to create concrete. The concrete is then 3D printed/sprayed onto the excavated tunnel to reinforce it. As soon as the tunnels are reinforced, the material between the tunnels can be removed in order to create a larger cavity that can be used for habitation. The proposed approach relies on design-to-robotic-production (D2RP) technology developed at TUD for on-Earth applications. The rhizomatic 3D-printed structure is a structurally optimized, porous shell structure with increased insulation properties. In order to regulate the indoor pressurised environment, an inflatable structure is placed inside the 3D-printed cavity. This inflatable structure is made of materials that can at some point also be produced on Mars via ISRU. Depending on location, the habitat and the production system are powered by a system combining solar and kite-power. The ultimate goal is to develop an autarkic D2RP system for building subsurface autarkic habitats on Mars from locally-obtained materials.
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In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several meters thick. Technical University Delft (TUD) proposes to excavate into the ground to create subsurface habitats. By excavating, not only can natural protection from radiation be achieved but also thermal insulation, as the temperature is more stable underground. At the same time, valuable resources can be excavated via in-situ resource utilization (ISRU). In this process, a swarm of autonomous mobile robots excavate the ground in a downwards sloping spiral movement. The excavated regolith will be mixed with cement, which can be produced on Mars through ISRU, in order to create concrete. The concrete is then 3D printed/sprayed onto the excavated tunnel to reinforce it. As soon as the tunnels are reinforced, the material between the tunnels can be removed in order to create a larger cavity that can be used for habitation. The proposed approach relies on design-to-robotic-production (D2RP) technology developed at TUD for on-Earth applications. The rhizomatic 3D-printed structure is a structurally optimized, porous shell structure with increased insulation properties. In order to regulate the indoor pressurised environment, an inflatable structure is placed inside the 3D-printed cavity. This inflatable structure is made of materials that can at some point also be produced on Mars via ISRU. Depending on location, the habitat and the production system are powered by a system combining solar and kite-power. The ultimate goal is to develop an autarkic D2RP system for building subsurface autarkic habitats on Mars from locally-obtained materials.
The Design-to-Robotic-Production and -Assembly (D2RP&A) process developed at Delft University of Technology (DUT) has been scaled up to building size by prototyping of-site a 3.30 m high fragment of a larger spaceframe structure The fragment consists of wooden linear elements connected to a polymer node printed at 3D Robot Printing and panels robotically milled at Amsterdam University of Applied Science (AUAS). It has been evaluated for suitability for assembly on-site without temporary support while relying on human-robot collaboration. The constructed architectural hybrid structure is proof of concept for an on- and off-site D2RP&A approach that is envisioned to be implemented using a range of robots able to possibly address all phases of construction in the future.
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The Design-to-Robotic-Production and -Assembly (D2RP&A) process developed at Delft University of Technology (DUT) has been scaled up to building size by prototyping of-site a 3.30 m high fragment of a larger spaceframe structure The fragment consists of wooden linear elements connected to a polymer node printed at 3D Robot Printing and panels robotically milled at Amsterdam University of Applied Science (AUAS). It has been evaluated for suitability for assembly on-site without temporary support while relying on human-robot collaboration. The constructed architectural hybrid structure is proof of concept for an on- and off-site D2RP&A approach that is envisioned to be implemented using a range of robots able to possibly address all phases of construction in the future.
Adaptive design strategies have been employed to improve structural performances in terms of load-bearing efficiency and energetic impact as well as to achieve multi-functionality. In this work, we investigate a passive adaptation strategy that employs variable stiffness in robotically printed materials. This paper focuses on the design and robotic fabrication of a chaise longue that can change shape to function as both recliner and chair depending on user requirements. The approach is unique in the way computational design is linked with robotic production. In this context, the design of the chaise longue is not limited to a formal process, but extends to the synthesis of the material distribution layout in order to achieve the intended functional behaviour.
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Adaptive design strategies have been employed to improve structural performances in terms of load-bearing efficiency and energetic impact as well as to achieve multi-functionality. In this work, we investigate a passive adaptation strategy that employs variable stiffness in robotically printed materials. This paper focuses on the design and robotic fabrication of a chaise longue that can change shape to function as both recliner and chair depending on user requirements. The approach is unique in the way computational design is linked with robotic production. In this context, the design of the chaise longue is not limited to a formal process, but extends to the synthesis of the material distribution layout in order to achieve the intended functional behaviour.
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