Three cooperative robotic fabrication methods for the scaffold-free construction of a masonry arch

Bruun, Edvard P.G.; Pastrana, Rafael; Paris, V.; Beghini, Alessandro; Pizzigoni, Attilio; Parascho, Stefana; Adriaenssens, Sigrid

doi:10.1016/j.autcon.2021.103803

Cited by 30 publications

(6 citation statements)

References 44 publications

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“…Assembly planning traditionally focuses on finding valid sequences to assemble objects [36], [37]. More recently, this was also applied to masonry constructions [38], [39]. Assembly sequence planning approaches have been scaled to large number of parts.…”

Section: B Assembly Planningmentioning

confidence: 99%

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

et al. 2023

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Robotic construction assembly planning aims to find feasible assembly sequences as well as the corresponding robotpaths and can be seen as a special case of task and motion planning (TAMP). As construction assembly can well be parallelized, it is desirable to plan for multiple robots acting concurrently. Solving TAMP instances with many robots and over a long time-horizon is challenging due to coordination constraints, and the difficulty of choosing the right task assignment. We present a planning system which enables parallelization of complex task and motion planning problems by iteratively solving smaller subproblems. Combining optimization methods to jointly solve for manipulation constraints with a sampling-based bi-directional space-time path planner enables us to plan cooperative multi-robot manipulation with unknown arrival-times. Thus, our solver allows for completing subproblems and tasks with differing timescales and synchronizes them effectively. We demonstrate the approach on multiple construction case-studies to show the robustness over long planning horizons and scalability to many objects and agents. Finally, we also demonstrate the execution of the computed plans on two robot arms to showcase the feasibility in the real world.

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Section: B Assembly Planningmentioning

confidence: 99%

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

et al. 2023

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“…Recently, various developments in robots and machines that can automatically build masonry and lay bricks have emerged. For example, Brunn et al [49] proposed scaffold-free construction of a masonry arch using a third robotic agent. Bruckmann and Boumann [50] simulated and optimized masonry construction using cable robots to stack building structure.…”

Section: Experimental Designmentioning

confidence: 99%

Productivity Measurement through IMU-Based Detailed Activity Recognition Using Machine Learning: A Case Study of Masonry Work

Hong,

Ham,

Chun

et al. 2023

Sensors

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Although measuring worker productivity is crucial, the measurement of the productivity of each worker is challenging due to their dispersion across various construction jobsites. This paper presents a framework for measuring productivity based on an inertial measurement unit (IMU) and activity classification. Two deep learning algorithms and three sensor combinations were utilized to identify and analyze the feasibility of the framework in masonry work. Using the proposed method, worker activity classification could be performed with a maximum accuracy of 96.70% using the convolutional neural network model with multiple sensors, and a minimum accuracy of 72.11% using the long short-term memory (LSTM) model with a single sensor. Productivity could be measured with an accuracy of up to 96.47%. The main contributions of this study are the proposal of a method for classifying detailed activities and an exploration of the effect of the number of IMU sensors used in measuring worker productivity.

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“…Examples for adaptive robotic manufacturing using higher-order knowledge systems include brick layout systems for masonry walls or robotic assembly concepts for timber joints. [42][43][44][45] Even 3D printing can be combined with intelligent behavior, for example, in transforming configurations for self-assembly and self-repair. 25 For navigation tasks, which are very important on construction sites, agents may use simultaneous localization and mapping (SLAM), where robots can navigate through unknown territory.…”

Section: Applications In Aec: Construction Robots and Other Examplesmentioning

confidence: 99%

“…As explained before, it is possible to use different robots as agents in CPS. Examples for adaptive robotic manufacturing using higher‐order knowledge systems include brick layout systems for masonry walls or robotic assembly concepts for timber joints 42–45 . Even 3D printing can be combined with intelligent behavior, for example, in transforming configurations for self‐assembly and self‐repair 25 .…”

Section: Applications In Aec: Construction Robots and Other Examplesmentioning

confidence: 99%

Self‐organizing systems in the construction industry

Lohmann

Kölzer

Schaan

et al. 2023

Engineering Reports

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Self‐organization is found in numerous natural and artificial systems. For the construction industry, self‐organizing processes are not only applicable in managing or organizing tasks, they also provide insight into materials or can be implemented into operations on building sites. In this paper, the terms feedback, agents, emergence and self‐organization are described to provide an insight into the complex processes relevant to a lot of fields in the construction industry. For this, the principles of adaptive processes are transferred to artificial systems. Besides self‐organization in building materials, an outlook is given to describe construction sites as cyber‐physical systems. Inside such systems, agents learn to organize work tasks more efficiently, particularly with the help of reinforcement learning. In this regard, a transfer of natural self‐organization—which also exist in materials—to building processes is made. A combination of natural and artificial systems is presented to promote self‐organization for various fields of application in the construction industry, especially for building sites.

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Three cooperative robotic fabrication methods for the scaffold-free construction of a masonry arch

Cited by 30 publications

References 44 publications

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

Productivity Measurement through IMU-Based Detailed Activity Recognition Using Machine Learning: A Case Study of Masonry Work

Self‐organizing systems in the construction industry

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