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Technology|Architecture + Design

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Robotic Control Strategies Applicable toArchitectural Design

Mathew Schwartz & Jaeheung Park

To cite this article: Mathew Schwartz & Jaeheung Park (2017) Robotic Control StrategiesApplicable to Architectural Design, Technology|Architecture + Design, 1:1, 73-82

To link to this article: http://dx.doi.org/10.1080/24751448.2017.1292796

Published online: 01 May 2017.

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Mathew SchwartzSeoul National University

Jaeheung ParkSeoul National University

While research in robotic control has produced numerous inventions and extensions of human ability, industrial robotic arms have had the larg-est effect within the architectural and design fields.  At this point, the development of custom end effectors for industrial robot arms are the most frequent ways to research and create new forms.  This paper discusses the most common robots within robotic control research and relates them to the architectural discourse.  As shown, the uses for compliant robots in architecture go far beyond human worker safety. The paper con-cludes with a proposed classification of robotic architectural research; where the use of robots as a tool is distinct from the ability to create new designs through unique control methods.

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controlling robotic arms, the workflows that have been solved are extremely narrow within the robotics context. Most notably, postprocessors are almost entirely and solely applicable to fixed position and kinematic control. While these robots provide access to a robust control interface that, compared to the past, pro-vides seemingly endless possibilities, the rapidly advancing field of robotics research is demonstrating the limited use of such a specific type of robot. One possibility for the difference between uses of industrial robot arms and other categories of robotics research is the different development approaches. As Bolmsjo (2014) points out, robots for the service industry are intrinsical-ly built around adaptability and generalization on a broader scale such that they sense–plan–act rather than the preprogrammed industrial manufacturing robots with limited to no sensing.

In order to address the disconnect between the use of robot-ics in architectural research and the research done within the robotics field itself, an overview of the terms to be used is ben-eficial. A joint is the location of a rotational or translational axis on the robot, and a link is the hardware (body part) that is physical-ly separated by two joints. The degrees of freedom of the robot, referred to as the DOF, is the number of variables required to describe the system. In the case of a typical industrial robot, or any robot with an open chain configuration, meaning the links of the robot are connected in a continuous fashion and do not reconnect to previous ones, this is equal to the number of joints. In Figure 1, the description of a humanoid robot’s (Schwartz et al. 2014) joint numbers demonstrates an equal number of DOF. As the links of the robot are separated by joints, in cases in which a

Introduction

The use of robotics in architectural design is relatively new given the achievements of the past few decades of research on the topic and its successful industrial applications. More specifi-cally, in recent years the academic discourse within architecture and design around robotics has been focused primarily on the use of industrial robotic arms as a way to explore new forms and construction techniques that were difficult or impossible for human laborers and, as such, extended the designer’s creativity (Bloss 2014). This includes both goals in which the given form is computationally generated and difficult for humans to create in physical space as well as high-precision, high-tolerance require-ments. Even though unmanned aerial vehicles (UAVs), com-monly referred to as drones, and custom robot manipulators have been used within the field of architecture, industrial robotic arms such as those developed by KUKA, Staublii, and ABB have dominated the academic scene. While initially the use of these robotic manipulators for manufacturing processes such as com-puter numerically controlled (CNC) milling provided discourse on methods of form finding, such as new joint connections between materials and multidimensional facades, recent advances have centered largely on the extension of the robotic arm capabili-ties through implementations of custom end effectors. Similarly, Raspall (2015) suggests that the transition from instrumentation to implementation is due to many of the challenges having been solved, with the example of the postprocessors available today.

While there have been great advances in accessibility for

v Figure 1 (Previous Page). Joint, link, and base description of a humanoid robot. Joints 2 and 3 intersect and do not have a link in between, while joints 3 and 4 have a link. Likewise, joints 4 and 5 have a link in between, while joints 5 and 6 intersect. Drawing by the authors.

v Figure 2. General industrial robot on a fixed track. The joints, base, and linear axis are labeled. As the industrial arm is not mobile and has a fixed link length, the track is able to extend the possible working area (reach) of the robot. Drawing by the authors.

w Figure 3. Variables and results used in forward and inverse kinematic calculations. Drawing by the authors.

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the final position and orientation of the end effector. Conversely, the IK method determines the joint angles from a given position and orientation of the end effector (Figure 3).

In both FK and IK the hardware implementation for moving a motor can be largely abstracted as the only required commands are to the positioning of the motor. An alternative approach to FK and IK is through dynamics calculations. By combining the mass of each link, along with the desired configuration and force, the amount of torque each motor should produce can be calculat-ed. This method, referred to as torque control, requires a more detailed level of access to the motors than kinematic control. For implementation details on a variety of control methods for indus-trial robots, see Ajwad et al. (2014).

Because of the access required to the motor, industrial robots most often restrict direct access and instead will develop an API or software wrapper to control the robot within a specification. Furthermore, the force required of a conventional motion is rare-ly a higher priority than positional accuracy of the end effector in a manufacturing setting, making an IK-based control method the most straightforward approach. However, large and forward-thinking companies such as KUKA have envisioned a “future pro-duction assistant,” as opposed to the classical industrial robot in which the manipulator is flexibly relocatable, frequently changing tasks, and both interacting with people and providing force/pre-cision assistance (Bischoff et al. 2010). This vision produced the KUKA-DLR lightweight robot arm, offering the ability to control the robot with a dynamic model, unlike the industrial robots fre-quently used within architecture and design.

When a position-based control method such as IK is integrat-ed with force sensors, many of the benefits of torque control can be replicated. The most commonly discussed is the ability of the robot to be compliant. In other words, the robot will perform a given task, while complying with external forces above a specified threshold. These forces can be as basic as gravity to as complex as a person walking into the manipulator. As a general example, if a robot was given a task to excavate a historic site in which build-ing components are underground, the robot can be commanded to exert enough force to dig through the dirt, but not enough to damage the building materials lying underneath (Figure 4).

In hardware, rather than a response to a signal, the torque of the actual robot is limited and as such is ideal in cases where a fast reac-tion time to prevent a higher torque is required. Another benefit of a hardware implementation of compliance is the ability to use a stand-alone robot arm without additional sensors. In the integrat-ed IK and sensor approach, a high-quality sensor can be used for increased accuracy of the force being applied but may incur higher undesirable force at the moment of impact. In essence, the differ-ence can be thought of in this way: a person walking in the dark can walk at a normal pace and stop when they feel a wall as to not injure themselves, or they can walk at a slow enough pace that they would not be injured even when walking into the wall. Because the latter is a matter of human safety (Vasic and Billard 2013), research has gone beyond feedback response through software and implement-ed compliance through hardware as well (Parmiggiani et al. 2014). Both active and passive compliance are useful in specific situations, while active compliance has the benefit of easily incorporating the forces into the control system (Wang, Loh, and Gu, 1998). From

certain location of the robot, such as the hip joint, should act in more than one axis, there is no link. As such, joints 2 and 3 do not have a link in between, while joints 3 and 4 do. In the case of a human shoulder, the ball-and-socket joint allows for free rotations in all three axes, while the common robot uses motors that can rotate along one axis. A common method of increasing the DOF in a specific place is to have multiple motors aligned such that the axis of each individual joint intersects.

The term manipulator is used to describe the combination of joints, also commonly referred to as an arm. The base of the manip-ulator is the location of the fixed position of the first joint, and the end effector is the last link of the robot, past the last joint. The term mobile refers to overall mobility of the robot in such a way that it is unconstrained from a set path such as a linear track con-nected to the ground. Finally, an n axis robot refers to the DOF of the manipulator, where an n+m axis robot is the n DOF of the manipulator with m number of additional DOF acting outside the manipulator links. In the case of a 6+1 robot, the manipulator has 6 DOF with the base of the manipulator attached to a linear track allowing for translational motion as an additional DOF, as seen in Figure 2. When a robotic arm is attached to a base with wheels or another type of free-moving platform, or in the case of a human-oid with legs (Figure 1), the robot is considered to be mobile, with the former being referred to specifically as a mobile manipulator.

Beyond the physical description of a robot, a method of con-trolling the described robot is needed. A variety of techniques exist, with new ones continually being developed. In this paper, some of the most common and well-defined techniques will be introduced in the next section. Following the control methods overview, a review of research within architecture is analyzed and described. Finally, key work that demonstrates a strong integra-tion of both fabrication and robotic control is presented.

Control Methods

From the very beginning of the development of robotic controls, two very distinct approaches were established: kinematic con-trol and dynamic control. While hybrid methods exist, these two approaches achieve robot control through different mathematical approaches. In the kinematic approach, the robot is commanded through specifying joint angles. Two methods for finding these joint angles are forward kinematics (FK) and inverse kinematics (IK). In the FK approach, a set of joint angles is used to determine

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v Figure 4. Left: Top plane represents the ground, circle represents a pipe or cable. A is the area of soil with a certain resistance, and B is the high resistance of the building material.

Right: The blue line represents the constant resistive force of soil in relation to depth, matching with the blue line approaching the pipe on the left diagram. The dashed blue line represents the predicted path. The red line represents the high resistive force of the pipe, where more force is not correlated with more depth during digging, matching the red dot on the left diagram. The shaded blue represents a possible force/depth strategy to ensure that the robot does not apply more force than should be required, and the shaded red area represents a dangerous failure from high force applied to the building material. Drawing by the authors.

v Figure 5. A: Force of gravity acting on the robot itself. B: Force of the material held by the robot. When both of (and only) these are compensated for, the robot will act compliant when another force, such as a person positioning the material, is applied. Drawing by the authors.

a fabrication perspective, beyond compliance and collaborative robot for safety, using compliant motion such as gravity compen-sation while including weight of the material, the robot can act as a holding jig to be manually placed and hold material in any posi-tion while either a human or secondary robot performs additional operations (Figure 5).

By moving the robotic arm onto a mobile base, the control meth-ods and approach to manufacturing can be completely changed. This is due to the uncertainty of the manipulator location relative to the desired task location. The problem is compounded when considering slippage and inaccurate or uncontrolled movement between the ground and the mobile base, in which case the use of vision or specific control techniques beyond that used in tradi-tional manufacturing must be implemented. Specific task require-ments could benefit from a mobile manipulator include but are not limited to a frequently changing environment, long-distance travel for components, working collaboratively and alongside people (Schneier and Bostelman 2015), and those in the construction industry such as rebuilding in areas after natural and man-made disasters (Ardiny, Witwicki, and Mondada 2015). Ardiny et al. also pointed out that mobile robots are capable of acting upon a space much greater than their physical length.

As early as 1989 research into grasping methods in manufac-turing saw a wide range of approaches to manipulating a variety of object shapes. In the case of hand manipulation, the research outlines nine definitions of analytical measures: compliance, con-nectivity, force closure, form closure, grasp isotropy, internal forces, manipulability, resistance to slipping, and stability (Cut-kosky 1989). More recent work into grasping has shown that the grasping motion of a human can be reduced mathematically using

a principle known as synergies (Kim et al. 2016). In essence, the idea of a large database of motions or a unique control strategy for multiple grasping motions is not required. This type of research holds significant value for robotic work in which a variety of materi-als and objects need to be held as well as when materials or object properties are not fully known. A common demonstration of this technique is in the difference between holding a cup full of liquid, in which the robot should maintain a firm grasp around the solid cup, versus grasping an egg, in which too strong a grasp will break the egg. Similarly, materials in fabrication vary widely, and while a sheet of foam insulation may have the same thickness as a 2×4, the amount of pressure needed to hold onto the 2×4 may crush the foam insulation.

A relatively recent area of research in robotics, and in particu-lar humanoids, has been whole-body control (Khatib et al. 2004). In this system, the dynamics of the robot are taken into account, as well as parameters regarding balance and motion. This technique creates an integrated system of parts in which action onto one part is compensated by actions on other parts. A specific exam-ple of this was demonstrated when a whole-body control meth-od implemented on a humanoid robot automatically created arm swinging during gait due to a rotational torque applied to the feet (Park 2008). Whole-body control can provide the capability of simultaneously controlling contact forces and motion. This capa-bility is especially useful in the event that the robot is required to execute both locomotion and manipulation in an uncertain envi-ronment such as a construction site, where the ground may be uneven and cluttered. It is an important and challenging issue that a robot move and perform tasks efficiently while being aware of its uncertain and changing environment.

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Similarly, when a given task may put people in danger, teleopera-tion may be used to offset these risks. Using a combination of tele-operation and control techniques described earlier, many teams in the DARPA robotics challenge were able to perform tasks such as opening a door and turning a valve (Johnson et al. 2015). This technique, as well as many other combinations of the control meth-ods described in this section have and could be researched further and applied to the architectural space. Until robots are completely autonomous in every task, the semiautonomous teleoperation of a robot can provide safety to humans and possibly a more efficient way of working. As illustrated in Figure 8, analogous to a construc-tion site foreman, a user can monitor the activity of the robot and issue simple commands to perform a task. Like a security guard watching multiple security cameras, a single user could monitor multiple robots while issuing these basic commands.

Robotic Trends in Architecture

While robotics is an increasingly popular topic in architecture, the research on robotic control as it pertains to design is very limited. While some work has been done, the majority of past research has revolved around processes and methods. In the last five years, con-ferences and conference topics relating to the use of robotics in architecture has steadily increased. In this section, a review of the main conference on robotics in architecture is presented with key research papers. While robotics work can be found in many other architectural academic venues such as ACADIA or eCAADe, the RobArch conference provides a general overview of key trends.

Beginning in 2012, the Association for Robots in Architecture launched the biannual robotics conference RobArch (Brell-Cokcan

Furthering research in uncertain environments, the peg-in-hole problem requires a robot arm to grasp a peg and place it in a hole with no knowledge of the environment or computer vision (Figure 6). This is achieved through contact forces when the robot moves the peg around the surface containing the hole (Park et al. 2015). A simple way to visualize this technique is by a person performing the same action. Given a peg and a hole in a table, a person can move the peg around the table without seeing the hole. When the peg runs over the hole, a sharp but slight drop will occur between the edge of the peg and the hole. As the peg is rotated around, the edges of the hole can be understood, and the peg can be placed within it. While this task may seem simple, the control methods required to perform it are not trivial. These methods are, however, applicable to numerous construction methods, the most obvious of which is a robotic arm placing a screw in a drilled hole, in which case the robot is both performing an action of placing a screw and at the same time using the failed attempts to sense the proper loca-tion of the screw.

Finally, the ability to operate a robot from another location is referred to as teleoperation. A simple implementation of this method would be a one-to-one mapping of joint angles in which a miniaturized version of a robotic arm is manually manipulated, and the corresponding full-scale version mimics. More unique implementations of teleoperation, such as the use of a haptic device to aid in medical procedures, have also been researched (Conti, Park, and Khatib 2014). The motion and pressure required of a doctor’s hand during ultrasounds in order to have proper images can have debilitating effects on the wrist and by offsetting the pressure to a robot these effects can be reduced, as illustrated in Figure 7.

v Figure 6. Robot moves peg straight toward the hole. Photograph by Ji-Hun Bae, Robotics R&D Group, Korea Institute of Industrial Technology. Reproduced with permission.

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and Braumann 2013), the first conference in architecture designated for robotics proj-ects and research. There have been three conferences, and the progression of robotics work within the field can be seen through the publications. The conference proceedings are structured into multiple groups, one of which is the scientific papers, also referred to as research papers, regarded as having a significant academic contribution. In the first confer-ence, nine research papers were accepted, five of which use a custom end effector as the main contribution to the robotics side. For example, focused on the process of mold making, the path planning of the robot in RoboSculpt was done using CAM software with the use of a custom end effector designed to act as a sculpting tool (Schwartz and Prasad 2012). Furthermore, studies such as that by Johns and Foley (2013) use a custom vacuum gripper to hold tiles in place while foam cures. The result is a still manually intensive and lengthy process that uses the robotic arm as a tile place holder through designated predefined coor-dinates. Finally, two papers discussed the use of computer vision for integration with the fabrication process; however, it was limited to a manual integration (Dubor and Diaz 2013) or limited to a single axis of information (Dierichs, Schwinn, and Menges 2013).

With twelve scientific papers accepted, the 2014 RobArch conference saw a slight increase in the proceedings output (McGee and Ponce de Leon 2014). Through these proceedings, it can be seen that a lack of research into robotics itself creates an issue of similarity between projects in which material or process is the main focus. For example, Clifford et al. (2014) and Schwartz and Prasad (2012) make similar claims to minimizing waste while manufacturing of fiberglass casts for customized molds. Neither paper pro-vides statistical analysis on benefits of the respective system or any quantitative data that enables other researchers to compare new techniques. Similarly, Johns and Foley (2014) present a method for using a bandsaw attached to the robot for cutting wood. As the kerf of the bandsaw blade is extremely small, a minimal amount of material is removed or wasted during the manufacturing process. The paper discusses techniques for dividing geometry suitable for the process but provides no further contribution to robotic control. With the close similarity of the bandsaw blade and hot knife or hot wire cutters, the con-tribution to sectioning geometry is transferable from the bandsaw to the foam, although not always from foam to bandsaw due to the single direction of the cutting blade.

By 2016, a wide variety of research projects were presented, with nine papers in the

r Figure 7. A haptic device can control the robot through the end effector desired position, commanded by the user’s hand. Drawing by the authors.

w Figure 8. Top left: Computer program with a simple button layout to command the types of motion the robot should perform. Top right: User view of robot relative to the 3D scanned environment from the robot, which is used to interpret which motion should be performed. Bottom: Picture of the robot in space with the overlay depicting the view from the robot. Drawing by the authors.

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Integrating Engineering and Design

Within the manufacturing academic discourse, torque control has been used in a variety of ways. A direct reference to the concept of torque control is the applied torque to a screw. While manual torque wrenches are common, research has shown the value of an integrated solution in which the torque control of the machine calculates rotational displacement for thread-in depth as well as torque applied to the screw (Chen et al. 2014). One example of a well-integrated system of material understanding and robotic control is the ability to adjust robot trajectories based on a hybrid force/motion control system for friction stir welding that keeps a specific contact force throughout the process (Mendes et al. 2014).

A popular machining method in architecture is the use of hot wire cutters with foam. This technique requires a heated wire to cut through the foam material in a balance that preserves the ten-sion of the wire while minimizing material loss due to the wire’s heat (Brell-Cokcan and Braumann 2014). While this has been solved through empirical iteration, it is yet another avenue for which force feedback can provide a control method for automat-ic calibration. Likewise, Rust et al. (2016) took it one step further and demonstrated the potential for force-feedback integrated systems within the architectural context. The authors advanced the capability of wire cutting from ruled surfaces to complex geometries by simulating the material to hot wire interactions and then including this information in the feedback loop of the robot controller (Figure 9). The force acted upon the end effec-tor is then integrated in the feedback loop to control the velocity along the specified path. This work seems to be, to date, the best example in architectural design in which the integration of force-feedback enabled the creation of forms not previously possible with the same manufacturing method. Notably, the authors did not use the typical construction robots such as KUKA, but rath-er UR5 robotic arms, more commonly known in the engineering research fields.

While Batliner et al. (2015) discuss autonomous control of the robot through sensors and external input, the research is based on a controller stack in which commands are overwritten, rather than utilizing algorithms with embedded decisions, such as dynamics, for the control. However, this method allows the authors to introduce a manufacturing process in which neither preprogrammed kinematics nor dynamic control can be applied. By introducing a heat gun on the end effector with the intention to modify a wax form, the authors demonstrate an interaction in which physical feedback such as force sensors are not able to provide useful information. Similarly, the modification of the wax is unpredictable through a kinematic model, without a complex material simulation, requiring an external scanner to provide con-tinuous feedback to the controller. A more preprogrammed and controlled version, with a multistage setup consisting of a heat gun, forming tool (Weissenböck, 2015), and cooling fan, reintro-duces the possibilities for force feedback through the forming tool.

One clear distinction between the role of robotics research in mechanical or computer engineering and the research with-in architecture is the accepted purpose of the work. While both

scientific research section (Reinhardt, Saunders, and Burry 2016). Most notably, the use of UAVs was introduced for a load-bearing architectural structure (Mirjan et al. 2016). However, the only clear contribution from that paper to further work in the robotic space is the description of an active rope dispenser, analogous to the cus-tom end effectors of a robot, as they provided no information on how the UAV was controlled. Another paper outside the typical architecture projects used computer vision algorithms to detect, pick up, and place wooden sticks (Jeffers 2016). The paper demon-strates a sensor feedback loop, which is proposed as an on-site con-struction method; however, the exact application is unclear. Other papers focused on materials and processes or have similar control methods to those of the previous two conferences.

In all three proceedings combined, only two of the thirty sci-entific publications used something other than a fixed location industrial robot. Although not inherently problematic, the focus on this type of robot has limited the scope of work in which robots and architecture can be explored. One factor that has contribut-ed to the limited variety of robots is the ease of implementation when using industrial robots through tools such as KUKA|PRC (Braumann and Brell-Cokcan n.d.), HAL (Schwartz 2013), and the easy conversion from CNC to robots through G-code (Brell-Cokcan and Braumann 2014). This focus also suggests there is a great opportunity for future research within the architectural robotic space that incorporates mobile platforms for on-site fabri-cation as well as newly formed robots. As an example, while mate-rial removal during a CNC operation can influence the rate of machine movement, more specialized machining techniques such as those done on sandstone can also benefit from feedback as the abrasive tools used wear down and require recalibration (Brell-Cokcan and Braumann 2014).

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disciplines hold significant contributions in high regard, there is a difference in the way these contributions are acknowledged. If new robotics research in engineering allows for a machine to cut faster, or more precisely, it provides a valuable contribution. In architecture, the sole ability of the robot to cut faster has lit-tle merit or contribution to the academic discourse. Conversely, robotics research that allows for a new design to be fabricated that was not previously possible may be valuable because of the desire for this design, while in engineering the design holds little value in and of itself. As discussed previously, the merit of a torque controller for a screw to be precisely driven into an object (Chen et al. 2014) may have little value to the architectural discourse. Likewise, the ability to cut complex geometry with a hot wire (Brell-Cokcan and Braumann 2014; Rust et al. 2016) provides little in the context of mechanical engineering. However, both of these works offer valuable contributions to their respective aca-demic disciplines by researching control methods of robotics, and, in these cases specifically, the forces associated with a specific manufacturing process.

Conclusion

There are infinite combinations of end effectors and materials that can interact, and to further the contributions of research-ers in robotic manufacturing these interactions should be able to stand on their own merit as a contribution to a process, rather than a contribution to robotics. Moving forward, a distinction to robotic manufacturing in the architectural discourse must be

created in which materials and processes are separated from research into robotic control for emerging design. Similarly, a more robust discourse on the benefits of a system will help dis-tinguish these two aspects. By stating that a combination of end effector and material is possible, with no comparison to alterna-tive methods, further discourse on the topic is extremely difficult. Rather, validating the research of either a process or control tech-nique allows a faster progression within the academic space as a specific goal is set. In the case of material and end effector inter-action, researchers can compare the final form or object that was created with what has been possible in the past, while robotic con-trol research can emphasize the improvements to a process in a quantitative way. Naturally, it is possible for an individual research project to achieve both, but even within that context the introduc-tion of a new process and the corresponding control strategy can be explicitly defined as unique contributions.

The premise of a 6 or 6+1 axis robotic arm has been thorough-ly established at this point. It is well known that the capability of this configuration enables manufacturing processes in which multiple angles of approach are required or creating a direct link between virtual geometry and the physical world is desired. This is not inherently problematic; research papers such as that by Reinhardt et al. (2014) use a robotic arm to accomplish the main goal of sound modifications through geometry. While the authors acknowledge the use of a robotic arm, the research focus is on the acoustical properties and integrated process of the final form.

From the background presented in this article, a few opportu-nities for research in robotic architecture are presented. Namely, custom end effectors, or even standard ones, can be controlled for specific object manipulation. For example, the ability of a robot to grasp a metal rod such as rebar would be valuable in the con-struction space. Similarly, providing the same end effector the ability to grasp a cement trowel or operate a cement valve would push integration of on-site robotics further into a collaborative workflow by utilizing tools available at the location without need-ing custom end effectors for each specific task.

In Figure 10, the concepts in this paper can be seen. By parti-tioning a graph into a horizontal axis prioritizing robotics research and a vertical axis of design research, past and future research can be mapped. The four example locations listed are the top left quadrant representing a general architecture research scope, the bottom right representing the general engineering scope, the top right representing a combination of robotics and design research, and finally the top middle representing a majority of the architec-ture papers discussed previously in which the focus is on design research, while the contributions to robotics are limited as the robot performs tasks as a tool, similar to a CNC machine.

Using this system, a few of the papers discussed in the current section can be mapped. As seen in Figure 11, the hot wire cutting system that used empirical observations to dictate the control methods of the robot (Brell-Cokcan and Braumann 2014) is placed in the middle of the horizontal axis for its use of a robot while not contributing to robotics research, and high on the vertical axis for its contribution to the fabrication of a new design. Likewise, the use of a torque controller for screws under uncertain conditions (Chen et al. 2014) is placed further on the horizontal scale for its contri-bution to torque control methods, and slightly above the vertical

r Figure 9. Spatial wire cutting overview diagram. Drawing by Romana Rust, Gramazio Kohler Research, ETH Zurich. Reproduced with permission.

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baseline as the paper allows for new fabrication techniques. Finally, the research of Rust et al. (2016) is placed equally on the vertical axis with Brell-Cokcan and Braumann (2014) as it too leads to new design possibilities using a hot wire cutter, but it is further along the horizontal axis for the contribution in path planning of the robot with an integrated feedback loop.

With no specific values, this mapping system is abstract and relatively subjective. One important point to note is the constant-ly expanding axis of the map. As current research at some point becomes common knowledge, the axis expands and new contribu-tions are pushed further in each direction. The first uses of robots for fabrication offered at some point significant contributions as the path planning and methods for control during the fabrica-tion process were new. Ideally this structure can be used to put research projects into perspective, and from the standpoint of this paper, to push the boundary on both the horizontal and vertical axes at the same time.

Mathew Schwartz received his BFA in Sculpture and MSc in Architecture with a concentration in Digital Technology from the University of Michigan.  He worked as a generalist in the University of Michigan 3D lab from 2008 to 2011 and received a Project Fellowship from the Design Lab in 2012.  Since 2013, he has been a Research Scientist at the Advanced Institutes of Convergence Technology, Seoul National University, researching human factors and robotics in relation to Architecture. Jaeheung Park received his BS and MS degrees from Seoul National University and his PhD degree from Stanford Univer-sity. From 2006 to 2009, he was a researcher at the Stanford Artificial Intelligence Laboratory, while also working at Hansen Medical. He has been a professor at Seoul National University since 2009. His research interests lie in the areas of whole-body control, humanoid robots, compliant motion control, and robot-environment interaction.

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Ardiny, H., S. Witwicki, and F. Mondada. 2015. “Are Autonomous Mobile Robots Able to Take Over Construction? A Review.” International Journal of Robotics, Theory and Applications 4(3):10–21.

Batliner, Curime, MichaelJake Newsum, and M. C. Rehm. 2015. “Live: Synchronous Computing in Robot Driven Design.” In Real Time: Proceedings of the 33rd eCAADe Conference, vol. 2, September 16–18, 277–286.

Bischoff, R., J. Kurth, G. Schreiber, R. Koeppe, A. Albu-Schäffer, A. Beyer, et al. 2010. “The KUKA-DLR Lightweight Robot Arm: A New Reference Platform for Robotics Research and Manufacturing.” In Robotics (ISR), 2010, 41st International Symposium on and 2010 6th German Conference on Robotics (ROBOTIK), 1–8.

Bloss, R. 2014. “Robots Have Come to Architecture to Model, Construct, Fabricate and Offer New Approaches to Create Innovative Designs, Elements and Structures.” Industrial Robot: An International Journal 41(5):403–7.

Bolmsjo, G. 2014. “Reconfigurable and Flexible Industrial Robot Systems.” Advances in Robotics and Automation, 3: 117. doi:10.4172/2168-9695.1000117

Braumann, Johannes, and Sigrid Brell-Cokcan. 2011. Parametric Robot Control: Integrated CAD/CAM for Architectural Design. In Integration through Computation: Proceedings of the 31st Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), 242–251. Calgary/Banff, Canada: The University of Calgary.

Brell-Cokcan, S., and J. Braumann, eds. 2013. Robotic Fabrication in Architecture, Art and Design. Vienna: Springer.

Brell-Cokcan, S., and J. Braumann, eds. 2014. “Robotic Production Immanent Design: Creative Toolpath Design in Micro and Macro Scale.” In ACADIA 14: Design Agency, 23–25, 579–88.

Chen, C.-H., et al. 2014. “Fastening Torque Control for Robotic Screw Driver under Uncertain Environment.” In Control,

r Figure 10. Diagram of robotics to design research priority. Drawing by the authors.

r Figure 11. Locations of some discussed papers. Drawing by the authors.

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Automation and Systems (ICCAS), 2014 14th International Conference, 814–18.

Clifford, B., N. Ekmekjian, P. Little, and A. Manto. 2014. “Variable Carving Volume Casting.” In Robotic Fabrication in Architecture, Art and Design 2014. Cham: Springer International, 3–15. https://doi.org/10.1007/978-3-319-04663-1_1.

Conti, F., J. Park, and O. Khatib. 2014. “Interface Design and Control Strategies for a Robot Assisted Ultrasonic Examination System.” Experimental Robotics 79:97–113.

Cutkosky, M. R. 1989. “On Grasp Choice, Grasp Models, and the Design of Hands for Manufacturing Tasks.” IEEE Transactions on Robotics and Automation 5(3):269–79.

Dierichs, K., T. Schwinn, and A. Menges. 2013. “Robotic Pouring of Aggregate Structures.” In Rob | Arch 2012. Vienna: Springer, 196–205. https://doi.org/10.1007/978-3-7091-1465-0_23.

Dubor, A., and G.-B. Diaz. 2013. “Magnetic Architecture.” In Rob | Arch 2012. Vienna: Springer, 206–13. https://doi.org/10.1007/978-3-7091-1465-0_24.

Jeffers, M. 2016. “Autonomous Robotic Assembly with Variable Material Properties.” In Robotic Fabrication in Architecture, Art and Design 2016. Cham: Springer International, 48–61. https://doi.org/10.1007/978-3-319-26378-6_4.

Johns, R. L., and N. Foley. 2013. “Irregular Substrate Tiling.” In Rob | Arch 2012. Vienna: Springer, 222–29. https://doi.org/10.1007/978-3-7091-1465-0_26.

Johns, R. L., and N. Foley. 2014. “Bandsawn Bands.” In Robotic Fabrication in Architecture, Art and Design 2014. Cham: Springer International, 17–32. https://doi.org/10.1007/978-3-319-04663-1_2.

Johnson, M., B. Shrewsbury, S. Bertrand, T. Wu, D. Duran, M. Floyd, et al. 2015. “Team IHMC’s Lessons Learned from the DARPA Robotics Challenge Trials.” Journal of Field Robotics 32(2):192–208.

Khatib, O., L. Sentis, J. Park, and J. Warren. 2004. “Whole-Body Dynamic Behavior and Control of Human-Like Robots.” International Journal of Humanoid Robotics 1(1):29–43. https://doi.org/10.1142/S0219843604000058.

Kim, S., M. Kim, J. Lee, and J. Park. 2016. “Robot Hand Synergy Mapping Using Multi-Factor Model and EMG Signal.” Experimental Robotics 109:671–83.

McGee, W., and M. Ponce de Leon, eds. 2014. Robotic Fabrication in Architecture, Art and Design 2014. Cham: Springer International. https://doi.org/10.1007/978-3-319-04663-1.

Mendes, N., P. Neto, M. A. Simão, A. Loureiro, and J. N. Pires. 2014. “A Novel Friction Stir Welding Robotic Platform: Welding Polymeric Materials.” International Journal of Advanced Manufacturing Technology, 1–10 .

Mirjan, A., F. Augugliaro, R. D’Andrea, F. Gramazio, and M. Kohler. 2016. “Building a Bridge with Flying Robots.” In Robotic Fabrication in Architecture, Art and Design 2016. Cham: Springer International, 34–47. https://doi.org/10.1007/978-3-319-26378-6_3.

Park, H., P. K. Kim, J. Park, J.-R. Jang, Y.-D. Shin, J.-H. Bae, and M.-H. Baeg. 2015. “Robotic Peg-in-Hole Assembly by Hand Arm Coordination.” Journal of Korea Robotics Society 10(1):42–51. https://doi.org/10.7746/jkros.2015.10.1.042.

Park, J. 2008. “Synthesis of Natural Arm Swing Motion in Human Bipedal Walking.” Journal of Biomechanics 41(7):1417–26, https://doi.org/10.1016/j.jbiomech.2008.02.031.

Parmiggiani, A., M. Randazzo, L. Natale, and G. Metta. 2014.

“An Alternative Approach to Robot Safety.” In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 484–89.

Raspall, F. 2015. “A Procedural Framework for Design to Fabrication.” Automation in Construction 51:132–39.

Reinhardt, D., D. Cabrera, M. Niemelä, G. Ulacco, and A. Jung. 2014. “TriVoc.” In Robotic Fabrication in Architecture, Art and Design 2014. Cham: Springer International, 163–80. https://doi.org/10.1007/978-3-319-04663-1_11.

Reinhardt, D., R. Saunders, and J. Burry, eds. 2016. Robotic Fabrication in Architecture, Art and Design 2016. Cham: Springer International.

Rust, R., D. Jenny, F. Gramazio, and M. Kohler. 2016. “Spatial Wire Cutting: Cooperative Robotic Cutting of Non-Ruled Surface Geometries for Bespoke Building Components.” In Living Systems and Micro-Utopias: Towards Continuous Designing, Proceedings of the 21st International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2016), 529–38.

Schneier, M., and R. Bostelman. 2015. Literature Review of Mobile Robots for Manufacturing. New York: National Institute of Standards and Technology.

Schwartz, M., S. Hwang, Y. Lee, J. Won, S. Kim, and J. Park. 2014. “Aesthetic Design and Development of Humanoid Legged Robot.” In 2014 IEEE-RAS International Conference on Humanoid Robots, 13–19. https://doi.org/10.1109/HUMANOIDS.2014.7041311.

Schwartz, M., and J. Prasad. 2012. “RoboSculpt.” In Rob | Arch 2012. Vienna: Springer, 230–37. https://doi.org/10.1007/978-3-7091-1465-0_27.

Schwartz, T. 2013. “HAL.” In Rob | Arch 2012. Vienna: Springer, 92–101. https://doi.org/10.1007/978-3-7091-1465-0_8.

Vasic, M., and A. Billard. 2013. “Safety Issues in Human-Robot Interactions.” In Robotics and Automation (ICRA), 2013 IEEE International Conference, 197–204.

Wang, W., R. N. K. Loh, and E. Y. Gu. 1998. “Passive Compliance versus Active Compliance in Robot-Based Automated Assembly Systems.” Industrial Robot: An International Journal 25(1):48–57.

Weissenböck, R. 2015. “Robotic Design-Fabrication: Exploring Robotic Fabrication as a Dynamic Design Process.” In Real Time: Proceedings of the 33rd eCAADe Conference, 2 (September 2015): 309–18.

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