Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

Design and application of convergent cellular automata

Systems made of many interacting elements may display unanticipated emergent properties. A system for which the desired properties are the same as those which emerge will be inherently robust. Currently available techniques for designing emergent properties are prohibitively costly for all but the simplest systems. The self-assembly of biological cells into tissues and ultimately organisms is an example of a natural dynamic distributed system of which the primary emergent behaviour is a fully operational being. The distributed process that co-ordinates this self-assembly is morphogenesis. By analysing morphogenesis with a cellular automata model we deduce a means by which this self-organisation might be achieved. This mechanism is then adapted to the design of self-organising patterns, reliable electronic systems and self-assembling systems. The limitations of the design algorithm are analysed, as is a means to overcome them. The cost of this algorithm is discussed and finally demonstrated with the design of a reliable arithmetic logic unit and a self-assembling, self-repairing and metamorphosising robot made of 12,000 cells

Characteristics of pattern formation and evolution in approximations of physarum transport networks

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on Chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation. © 2010 Massachusetts Institute of Technology

KINE[SIS]TEM'17 From Nature to Architectural Matter

Kine[SiS]tem – From Kinesis + System. Kinesis is a non-linear movement or activity of an organism in response to a stimulus. A system is a set of interacting and interdependent agents forming a complex whole, delineated by its spatial and temporal boundaries, influenced by its environment. How can architectural systems moderate the external environment to enhance comfort conditions in a simple, sustainable and smart way? This is the starting question for the Kine[SiS]tem’17 – From Nature to Architectural Matter International Conference. For decades, architectural design was developed despite (and not with) the climate, based on mechanical heating and cooling. Today, the argument for net zero energy buildings needs very effective strategies to reduce energy requirements. The challenge ahead requires design processes that are built upon consolidated knowledge, make use of advanced technologies and are inspired by nature. These design processes should lead to responsive smart systems that deliver the best performance in each specific design scenario. To control solar radiation is one key factor in low-energy thermal comfort. Computational-controlled sensor-based kinetic surfaces are one of the possible answers to control solar energy in an effective way, within the scope of contradictory objectives throughout the year.FC

Designing parametric matter:Exploring adaptive material scale self-assembly through tuneable environments

3D designs can be created using generative processes, which can be transformed and adapted almost infinitely if they remain within their digital design software. For example, it is easy to alter a 3D object's colour, size, transparency, topology and geometry by adjusting values associated with those attributes. Significantly, these design processes can be seen as morphogenetic, where form is grown out of bottom-up logic’s and processes. However, when the designs created using these processes are fabricated using traditional manufacturing processes and materials they lose all of these abilities. For example, even the basic ability to change a shapes' size or colour is lost. This is partly because the relationships that govern the changes of a digital design are no longer present once fabricated. The motivating aim is: how can structures be grown and adapted throughout the fabrication processes using programmable self-assembly? In comparison the highly desirable attribute of physical adaptation and change is universally present within animals and biological processes. Various biological organisms and their systems (muscular or skeletal) can continually adapt to the world around them to meet changing demands across different ranges of time and to varying degrees. For example, a cuttlefish changes its skin colour and texture almost immediately to hide from predators. Muscles grow in response to exercise, and over longer time periods bones remodel and heal when broken, meaning biological structures can adapt to become more efficient at meeting regularly imposed demands. Emerging research is rethinking how digital designs are fabricated and the materials they are made from, leading to physically responsive and reconfigurable structures. This research establishes an interdisciplinary and novel methodology for building towards an adaptive design and fabrication system when utilising material scale computation process (e.g. self-assembly) within the fabrication process, which are guided by stimuli. In this context, adaption is the ability of a physical design (shape, pattern) to change its local material and or global properties, such as: shape, composition, texture and volume. Any changes to these properties are not predefined or constrained to set limits when subjected to environmental stimulus, (temperature, pH, magnetism, electrical current). Here, the stimulus is the fabrication mechanisms, which are governed and monitored by digital design tools. In doing so digital design tools will guide processes of material scale self-assembly and the resultant physical properties. The fabrication system is created through multiple experiments based on various material processes and platforms, from paint and additives, to ink diffusion and the mineral accretion process. A research through design methodology is used to develop the experiments, although the experiments by nature are explorative and incremental. Collectively they are a mixture of analogue and digital explorations, which establish principles and a method of how to grow physical designs, which can adapt based on digital augmentations by guiding material scale self-assembly. The results demonstrate that it is possible to grow physical 2D and 3D designs (shapes and patterns) that could have their properties tuned and adapted by creating tuneable environments to guide the mineral accretion process. Meaning, the desirable and dynamic traits of digital computational designs can be leveraged and extended the as they are made physical. Tuneable environments are developed and defined thought the series experiments within this thesis. Tuneable environments are not restricted to the mineral accretion process, as it is demonstrated how they can manipulate ink cloud patterns (liquid diffusion), which are less constrained in comparison to the mineral accretion process. This is possible due to the use of support mediums that dissipate energy and also contrast materially (they do not diffuse). Combining contrasting conditions (support mediums, resultant material effects) with the idea of tuneable environments reveals how: 1) material growth and properties can be monitored and 2) the possibilities of growing 3D designs using material scale self-assembly, which is not confined to a scaffold framework. The results and methodology highlight how tuneable environments can be applied to advance other areas of emerging research, such as altering environmental conditions during methods of additive manufacturing, such as, suspended deposition, rapid liquid printing, computed axial lithography or even some strategies of bioprinting. During the process, deposited materials and global properties could adapt because of changing conditions. Going further and combining it with the idea of contrasting mediums, this could lead to new types 3D holographic displays, which are grown and not restricted to scaffold frameworks. The results also point towards a potential future where buildings and infrastructure are part of a material ecosystem, which can share resources to meet fluctuating demands, such as, solar shading, traffic congestion, live loading

Chemotaxis-based spatial self-organization algorithms

Self-organization is a process that increases the order of a system as a result of local interactions among low-level, simple components, without the guidance of an outside source. Spatial self-organization is a process in which shapes and structures emerge at a global level from collective movements of low level shape primitives. Spatial self-organization is a stochastic process, and the outcome of the aggregation cannot necessarily be guaranteed. Despite the inherent ambiguity, self-organizing complex systems arise everywhere in nature. Motivated by the ability of living cells to form specific shapes and structures, we develop two self-organizing systems towards the ultimate goal of directing the spatial self-organizing process. We first develop a self-sorting system composed of a mixture of cells. The system consistently produces a sorted structure. We then extend the sorting system to a general shape formation system. To do so, we introduce morphogenetic primitives (MP), defined as software agents, which enable self-organizing shape formation of user-defined structures through a chemotaxis paradigm. One challenge that arises from the shape formation process is that the process may form two or more stable final configurations. In order to direct the self-organizing process, we find a way to characterize the macroscopic configuration of the MP swarm. We demonstrate that statistical moments of the primitives' locations can successfully capture the macroscopic structure of the aggregated shape. We do so by predicting the final configurations produced by our spatial self-organization system at an early stage in the process using features based on the statistical moments. At the next stage, we focus on developing a technique to control the outcome of bifurcating aggregations. We identify thresholds of the moments and generate biased initial conditions whose statistical moments meet the thresholds. By starting simulations with biased, random initial configurations, we successfully control the aggregation for a number of swarms produced by the agent-based shape formation system. This thesis demonstrates that chemotaxis can be used as a paradigm to create an agent- based spatial self-organization system. Furthermore, statistical moments of the swarm can be used to robustly predict and control the outcomes of the aggregation process.Ph.D., Computer Science -- Drexel University, 201