Printing-while-moving: a new paradigm for large-scale robotic 3D Printing

Building and Construction have recently become an exciting application ground for robotics. In particular, rapid progress in materials formulation and in robotics technology has made robotic 3D Printing of concrete a promising technique for in-situ construction. Yet, scalability remains an important hurdle to widespread adoption: the printing systems (gantry- based or arm-based) are often much larger than the structure to be printed, hence cumbersome. Recently, a mobile printing system - a manipulator mounted on a mobile base - was proposed to alleviate this issue: such a system, by moving its base, can potentially print a structure larger than itself. However, the proposed system could only print while being stationary, imposing thereby a limit on the size of structures that can be printed in a single take. Here, we develop a system that implements the printing-while-moving paradigm, which enables printing single-piece structures of arbitrary sizes with a single robot. This development requires solving motion planning, localization, and motion control problems that are specific to mobile 3D Printing. We report our framework to address those problems, and demonstrate, for the first time, a printing-while-moving experiment, wherein a 210 cm x 45 cm x 10 cm concrete structure is printed by a robot arm that has a reach of 87 cm.Comment: 6 pages, 7 figur

Autonomous Scene Understanding, Motion Planning, and Task Execution for Geometrically Adaptive Robotized Construction Work

The construction industry suffers from such problems as high cost, poor quality, prolonged duration, and substandard safety. Robots have the potential to help alleviate such problems by becoming construction co-workers, yet they are seldom found operating on today’s construction sites. This is primarily due to the industry’s unstructured nature, substantial scale, and loose tolerances, which present additional challenges for robot operation. To help construction robots overcome such challenges and begin functioning as useful partners in human-robot construction teams, this research focuses on advancing two fundamental capabilities: enabling a robot to determine where it is located as it moves about a construction site, and enabling it to determine the actual pose and geometry of its workpieces so it can adapt its work plan and perform work. Specifically, this research first explores the use of a camera-marker sensor system for construction robot localization. To provide a mobile construction robot with the ability to estimate its own pose, a camera-marker sensor system was developed that is affordable, reconfigurable, and functional in GNSS-denied locations, such as urban areas and indoors. Excavation was used as a case study construction activity, where bucket tooth pose served as the key point of interest. The sensor system underwent several iterations of design and testing, and was found capable of estimating bucket tooth position with centimeter-level accuracy. This research also explores a framework to enable a construction robot to leverage its sensors and Building Information Model (BIM) to perceive and autonomously model the actual pose and geometry of its workpieces. Autonomous motion planning and execution methods were also developed and incorporated into the adaptive framework to enable a robot to adapt its work plan to the circumstances it encounters and perform work. The adaptive framework was implemented on a real robot and evaluated using joint filling as a case study construction task. The robot was found capable of identifying the true pose and geometry of a construction joint with an accuracy of 0.11 millimeters and 1.1 degrees. The robot also demonstrated the ability to autonomously adapt its work plan and successfully fill the joint. In all, this research is expected to serve as a basis for enabling robots to function more effectively in challenging construction environments. In particular, this work focuses on enabling robots to operate with greater functionality and versatility using methods that are generalizable to a range of construction activities. This research establishes the foundational blocks needed for humans and robots to leverage their respective strengths and function together as effective construction partners, which will lead to ubiquitous collaborative human-robot teams operating on actual construction sites, and ultimately bring the industry closer to realizing the extensive benefits of robotics.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149785/1/klundeen_1.pd

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

Fabricate 2020

Fabricate 2020 is the fourth title in the FABRICATE series on the theme of digital fabrication and published in conjunction with a triennial conference (London, April 2020). The book features cutting-edge built projects and work-in-progress from both academia and practice. It brings together pioneers in design and making from across the fields of architecture, construction, engineering, manufacturing, materials technology and computation. Fabricate 2020 includes 32 illustrated articles punctuated by four conversations between world-leading experts from design to engineering, discussing themes such as drawing-to-production, behavioural composites, robotic assembly, and digital craft

Path and Motion Planning for Autonomous Mobile 3D Printing

Autonomous robotic construction was envisioned as early as the ‘90s, and yet, con- struction sites today look much alike ones half a century ago. Meanwhile, highly automated and efficient fabrication methods like Additive Manufacturing, or 3D Printing, have seen great success in conventional production. However, existing efforts to transfer printing technology to construction applications mainly rely on manufacturing-like machines and fail to utilise the capabilities of modern robotics. This thesis considers using Mobile Manipulator robots to perform large-scale Additive Manufacturing tasks. Comprised of an articulated arm and a mobile base, Mobile Manipulators, are unique in their simultaneous mobility and agility, which enables printing-in-motion, or Mobile 3D Printing. This is a 3D printing modality, where a robot deposits material along larger-than-self trajectories while in motion. Despite profound potential advantages over existing static manufacturing-like large- scale printers, Mobile 3D printing is underexplored. Therefore, this thesis tack- les Mobile 3D printing-specific challenges and proposes path and motion planning methodologies that allow this printing modality to be realised. The work details the development of Task-Consistent Path Planning that solves the problem of find- ing a valid robot-base path needed to print larger-than-self trajectories. A motion planning and control strategy is then proposed, utilising the robot-base paths found to inform an optimisation-based whole-body motion controller. Several Mobile 3D Printing robot prototypes are built throughout this work, and the overall path and motion planning strategy proposed is holistically evaluated in a series of large-scale 3D printing experiments

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

3D digital models 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 structure’s/object's colour, size, geometry and topology by adjusting values associated with those attributes. However, when these digital models are fabricated using traditional, highly deterministic fabrication processes, where form is imposed upon materials, the physical structure typically loses all of these adaptive abilities. These reduced physical abilities are primarily a result of how design representations are fabricated and if they can maintain relationships with the physical counterpart/materials post-fabrication. If relationships between design representations and physical materials are removed it can lead to redundancy and significant material waste as the material make-up of a physical structure can’t accommodate fluctuating design demands (e.g. aesthetics, structural, programmatic). This raises the question: how can structures be grown and adapted throughout fabrication processes using programmable self-assembly? This research explores and documents the development of an adaptive design and fabrication system through a series of ‘material probes’, which begin to address this aim. The series of material probes have been carried out using research through design as an approach, which enables an exploration and highlights challenges, developments and reflections of the design process as well as, the potentials of rethinking design and fabrication processes and their relationships with materials. Importantly, the material probes engage with material computation (e.g. self-assembly/autonomous-assembly) and demonstrate that various patterns, shapes and structures can have various material properties (e.g. volume, composition, texture, shape) tuned and adapted throughout the fabrication process by inducing stimuli (e.g. temperature, magnetism, electrical current) and altering parameters of stimuli (e.g. duration, magnitude, location). As a result, the structures created can tune and adapt their material properties across length scales and time scales. These adaptive capacities are enabled by creating what is termed ‘tuneable environments. Significantly, tuneable environments fundamentally rethink design and fabrication processes and their relationships with materials, since inducing stimuli and controlling their parameters can be used as an approach to creating programmable self-assembly. Consequently, the material platforms’ units of matter do not have to have pre-design properties (e.g. geometries, interfaces) This research points towards future potentials of structures that can physically evolve and lead to the decarbonising of urban contexts where they could behave like ‘living material eco-systems’, and resources are shared to meet fluctuating demands through passive means