H.H. Bier
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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.
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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.
The construction industry faces persistent productivity shortfalls and rising carbon dioxide emissions, which drives a shift toward the use of low-carbon materials and higher degrees of automation. Timber, a renewable and carbon-sequestering material, becomes especially compelling when combined with robotic fabrication. Although rapid advances have been implemented in the last decade, research and practice remain fragmented, and systematic evaluations of technological readiness are scarce. This gap is addressed in this review through critical literature synthesis of robotic timber construction, combining bibliometric analysis with a comparative evaluation of twelve representative case studies from 2020 to 2025. Computational and robotic tools are mapped across the design to fabrication pipeline, and emerging advancements are identified such as digital twins, real-time adaptive workflows, and machine learning driven fabrication, alongside discrete and circular strategies. Barriers to scale up are also assessed, including mid-level technology readiness, regulatory and safety obligations for human–robot interaction, evidence on cost and productivity, and workforce training needs. By clarifying the current level of robotization and specifying both research gaps and industrial prerequisites, this study provides a structured foundation for the next phase of development. It helps scholars by consolidating methods and metrics for rigorous evaluation, and it helps practitioners by highlighting pathways to scalable, certifiable, and circular deployment that align cost, safety, and training requirements.
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The construction industry faces persistent productivity shortfalls and rising carbon dioxide emissions, which drives a shift toward the use of low-carbon materials and higher degrees of automation. Timber, a renewable and carbon-sequestering material, becomes especially compelling when combined with robotic fabrication. Although rapid advances have been implemented in the last decade, research and practice remain fragmented, and systematic evaluations of technological readiness are scarce. This gap is addressed in this review through critical literature synthesis of robotic timber construction, combining bibliometric analysis with a comparative evaluation of twelve representative case studies from 2020 to 2025. Computational and robotic tools are mapped across the design to fabrication pipeline, and emerging advancements are identified such as digital twins, real-time adaptive workflows, and machine learning driven fabrication, alongside discrete and circular strategies. Barriers to scale up are also assessed, including mid-level technology readiness, regulatory and safety obligations for human–robot interaction, evidence on cost and productivity, and workforce training needs. By clarifying the current level of robotization and specifying both research gaps and industrial prerequisites, this study provides a structured foundation for the next phase of development. It helps scholars by consolidating methods and metrics for rigorous evaluation, and it helps practitioners by highlighting pathways to scalable, certifiable, and circular deployment that align cost, safety, and training requirements.
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.
Advancements in 3D printing technology facilitate the implementation of innovative building processes. When combined with circular approaches in particular the use of recycled materials, significant reduction of environmental impact is expected. This paper presents an investigation into the potential of recycled materials for 3D printing habitats. The study’s main objective is to assess two recycled materials, concrete and sandstone, which are suitable for 3D printing. Through comparative analysis, the research aims to demonstrate the environmental impact and process feasibility of each material in the context of 3D printing. The methodology involves the evaluation of recycled concrete and sandstone regarding material properties and overall environmental footprint by comparing building components such as columns. The energy use and carbon footprint in 3D printing are evaluated with the goal to minimize waste and contribute to a closed-loop approach. One of the fundamental aspects of this assessment involves quantifying and comparing the carbon dioxide (CO2) emissions associated with each material at some stages of its life cycle, i.e., from material extraction to assembly. Consequently, by analyzing quantitative data, a basis for a more environmentally friendly circular approach for printing habitats is determined.
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Advancements in 3D printing technology facilitate the implementation of innovative building processes. When combined with circular approaches in particular the use of recycled materials, significant reduction of environmental impact is expected. This paper presents an investigation into the potential of recycled materials for 3D printing habitats. The study’s main objective is to assess two recycled materials, concrete and sandstone, which are suitable for 3D printing. Through comparative analysis, the research aims to demonstrate the environmental impact and process feasibility of each material in the context of 3D printing. The methodology involves the evaluation of recycled concrete and sandstone regarding material properties and overall environmental footprint by comparing building components such as columns. The energy use and carbon footprint in 3D printing are evaluated with the goal to minimize waste and contribute to a closed-loop approach. One of the fundamental aspects of this assessment involves quantifying and comparing the carbon dioxide (CO2) emissions associated with each material at some stages of its life cycle, i.e., from material extraction to assembly. Consequently, by analyzing quantitative data, a basis for a more environmentally friendly circular approach for printing habitats is determined.
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.
Conference paper
(2024)
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Giuseppe Calabrese, Arwin Hidding, Henriette Bier, Casper van Engelenburg, Seyran Khademi, Atousa Aslaminezhad
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.
Editorial CpA #6
Human-Robot Interaction for Carbon-free Architecture
The Spool CpA #6 issue on Human-Robot Interaction for Carbon-free Architecture reviews current tendencies in autonomous construction and human-robotic interaction in architecture. It aims at affirming and/or challenging research agendas in the domain of architectural robots and attempts to answer questions about (i) the fundamental framing of post-carbon autonomous construction, (ii) the interdependencies between machines, humans, and materials, and (iii) the different imple-mentation timeframes ranging from continuous transformation to leapfrogging.
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The Spool CpA #6 issue on Human-Robot Interaction for Carbon-free Architecture reviews current tendencies in autonomous construction and human-robotic interaction in architecture. It aims at affirming and/or challenging research agendas in the domain of architectural robots and attempts to answer questions about (i) the fundamental framing of post-carbon autonomous construction, (ii) the interdependencies between machines, humans, and materials, and (iii) the different imple-mentation timeframes ranging from continuous transformation to leapfrogging.
Journal article
(2024)
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Henriette Bier, Arwin Hidding, Seyran Khademi, Casper van Engelenburg, Hamed Alavi, Sailin Zhong
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.
Conference paper
(2024)
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H.H. Bier, A.J. Hidding, S. Khademi, C.C.J. van Engelenburg, J.M. Prendergast, L. Peternel
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.
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.
Journal article
(2024)
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Henriette Bier, Arwin Hidding, Stijn Brancart, Alessandra Luna-Navarro, Seyran Khademi, Casper van Engelenburg
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.
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.
Dialogues on Architecture, published in various issues of Spool CpA, is a series of dialogues between researchers and practitioners, who are embracing the intellectual model of high technology and are involved in its advancement and application in architecture. Dialog #6 presents discussions risen during an online symposium on challenges of the Architecture, Engineering and Construction (AEC) industry, which is facing a threefold challenge involving the (i) digital transformation of all design and planning processes, (ii) automation of construction processes, and (iii) reconsideration of energy, process, and material use. These challenges involve issues with respect to productivity, scalability, safety, labour skill shift, and environmental impact. Acknowledging that there is a particular urgency in transferring effective solutions from research to building practice to meet significant carbon reduction goals by 2040, the one-day symposium organized as an online event in 2022
1, Human-Robot Interaction for Post-Carbon Architecture (HRI4PCA), was an opportunity to make an inventory of current tendencies in autonomous construction and human-robotic interaction in architecture. It aims at affirming and/or challenging research agendas in the domain of architectural robots.
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Dialogues on Architecture, published in various issues of Spool CpA, is a series of dialogues between researchers and practitioners, who are embracing the intellectual model of high technology and are involved in its advancement and application in architecture. Dialog #6 presents discussions risen during an online symposium on challenges of the Architecture, Engineering and Construction (AEC) industry, which is facing a threefold challenge involving the (i) digital transformation of all design and planning processes, (ii) automation of construction processes, and (iii) reconsideration of energy, process, and material use. These challenges involve issues with respect to productivity, scalability, safety, labour skill shift, and environmental impact. Acknowledging that there is a particular urgency in transferring effective solutions from research to building practice to meet significant carbon reduction goals by 2040, the one-day symposium organized as an online event in 2022 1, Human-Robot Interaction for Post-Carbon Architecture (HRI4PCA), was an opportunity to make an inventory of current tendencies in autonomous construction and human-robotic interaction in architecture. It aims at affirming and/or challenging research agendas in the domain of architectural robots.
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.
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.
Book chapter
(2023)
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Henriette Bier, A.J. Hidding, M.T.C. Latour, P.I.J. Oskam, Hamed S. Alavi, A. Külekci
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.
Robotic systems are increasingly incorporated into building processes and buildings. The question for the future is thus not if but how robotic systems will be integrated into architecture and the built environment. Such systems have a major impact due to the convergence of multiple technologies such as artificial intelligence (AI), large-scale machine-to-machine and human-to-machine communication (M2M and H2M), and the Internet of Things (IoT). Implications are explored and presented in this section in relationship to historical and theoretical interpretations and current manifestations by presenting ongoing research implemented at institutions such as McGill and Cornell Universities from North America, Technical University Delft from Europe, and the Chinese University of Hong Kong from Asia.
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Robotic systems are increasingly incorporated into building processes and buildings. The question for the future is thus not if but how robotic systems will be integrated into architecture and the built environment. Such systems have a major impact due to the convergence of multiple technologies such as artificial intelligence (AI), large-scale machine-to-machine and human-to-machine communication (M2M and H2M), and the Internet of Things (IoT). Implications are explored and presented in this section in relationship to historical and theoretical interpretations and current manifestations by presenting ongoing research implemented at institutions such as McGill and Cornell Universities from North America, Technical University Delft from Europe, and the Chinese University of Hong Kong from Asia.
Rapid urbanization with the associated land cover and land use change, as well as resource depletion, contribute to the degradation of ecosystems and biodiversity and have a negative impact on human health and well-being. Societal calls for responses and results pose a significant challenge for research and education in the various fields concerned with the environment. Alongside the current environmental crisis there is a pressing need for developing ‘green solutions’ for the built environment with the help of data-driven methods, workflows and tools.
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Rapid urbanization with the associated land cover and land use change, as well as resource depletion, contribute to the degradation of ecosystems and biodiversity and have a negative impact on human health and well-being. Societal calls for responses and results pose a significant challenge for research and education in the various fields concerned with the environment. Alongside the current environmental crisis there is a pressing need for developing ‘green solutions’ for the built environment with the help of data-driven methods, workflows and tools.