Robotized Additive Manufacturing of Funicular Architectural Geometries Based on Building Materials

Lakhal, Othman; Chettibi, Taha; Belarouci, Abdelkader; Dherbomez, Gérald

doi:10.1109/tmech.2020.2974057

Cited by 18 publications

(5 citation statements)

References 26 publications

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“…Other strategies are also employed in construction sites. For instance, SLAM-based (Simultaneous Localization and Mapping) [18] methods are used by some researchers for the localization of mobile construction robots [19][20][21]. QuicaBot, which is used to inspect the quality of buildings, employed SLAM algorithms to achieve simultaneous positioning of the robot and generated environmental maps [22].…”

Section: Heterogeneous Wall Brickworkmentioning

confidence: 99%

An Improved Trilateral Localization Technique Fusing Extended Kalman Filter for Mobile Construction Robot

Zeng,

Guo,

Zhu

et al. 2024

Buildings

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Semi-open and chaotic environments of building sites are considered primary challenges for the localization of mobile construction robots. To mitigate environmental limitations, an improved trilateral localization technique based on artificial landmarks fusing the extended Kalman filters (EKFs) is proposed in this paper. The reflective intensity of the onboard laser is employed to identify artificial landmarks arranged in the ongoing construction environment. A trilateral positioning algorithm is then adopted and evaluated based on artificial landmarks. Multi-sensor fusion, combined with the EKF, is included to improve the positioning accuracy and reliability of the robot in complex conditions. We constructed validation scenarios in the Gazebo simulation environment to verify the required localization functionality. Concurrently, we established simulated testing environments in real-world settings, where the practicality of the proposed technique was validated through the fitting of ideal and actual localization trajectories. The effectiveness of the proposed technique was corroborated through comparative experimental results.

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Section: Heterogeneous Wall Brickworkmentioning

confidence: 99%

An Improved Trilateral Localization Technique Fusing Extended Kalman Filter for Mobile Construction Robot

Zeng,

Guo,

Zhu

et al. 2024

Buildings

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“…In recent years, the application of industrial robots in the industrial field has become increasingly widespread [6]. For instance, robots are not only used in traditional industrial sectors such as welding, assembly, and material handling, but in recent years, robots have also been used in emerging fields such as 3D printing [7][8][9] and 3D scanning [10]. This is primarily due to the variety of industrial robots and their high degree of freedom, allowing them to meet various application scenarios.…”

Section: Prior Artmentioning

confidence: 99%

Vision Based Trajectory Dynamic Compensation System of Industrial Robot

Zhao,

Murakami,

Yamakawa

2023

Preprint

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This study aims to enhance the flexibility of robots in the manufacturing process to meet the growing demand for flexible manufacturing systems by constructing a dynamic compensation system. The system enables the end effector of the robot to track the trajectory contour on the horizontal plane, even if there is a deviation between the teaching trajectory and the target trajectory contour. The proposed system employs an innovative mechanism design and algorithm that enables dynamic compensation of the robot's absolute position in the XY-plane, even when the end effector is obstructed. The system uses an XY-stage and two industrial cameras, with each axis being separately controlled. To detect and compensate for errors in the end effector and target trajectory, the two cameras are aligned with the X- and Y-direction linear stage, respectively. The cameras are fixed with respect to the linear stage, and the end effector is placed on the stage work surface. Unlike traditional stereo cameras, the cameras in this system do not require calibration for their positional relationship. To verify the system's effectiveness, this study set a group of teaching and target trajectory contours with a maximum deviation of over than 8mm. Under the compensation of the system, the maximum error between the end effector and the target trajectory contour was 22.8 pixels (1.34mm), with an average absolute error of 5.4 pixels (0.32mm). Compared to the maximum error of 8.45mm before compensation, the error has been reduced by 84%.

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“…In particular, robotic arms have been implemented in the process, allowing for higher control (i.e., orientation of the printing head in a desired way to print volumetrically). Such an approach is quite common in the construction field, in which concrete and clay-like materials are extruded with the support of robots [11][12][13][14]. Few attempts towards robotic AM implementation have been made in small-scale manufacturing.…”

Section: Introductionmentioning

confidence: 99%

RAVEN: development of a novel volumetric extrusion-based system for small-scale Additive Manufacturing

Fucile¹,

David²,

Kalogeropoulou³

et al. 2023

Preprint

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Recent technological advances in the field of Additive Manufacturing (AM) and the increasing need in Regenerative Medicine (RM) for devices that better and better mimic native tissues architecture are showing limitations in the current scaffolds fabrication techniques. A switch from the typical layer-by-layer approach is needed to achieve precise control on fibers orientation and pores dimension and morphology. In this work a new AM apparatus, the RAVEN (Robot-Assisted Volumetric ExtrusioN) system, is presented. RAVEN is based on a 7-DOF robotic arm and an FDM extruder and allows for volumetric extrusion of polymeric filaments. The development process, namely the robotic motion optimization, the optimization towards small-scale trajectories, the custom-made hardware/software interfaces, and the different printing capabilities are hereby presented. The successful results are promising towards future advanced applications such as in vivo bioprinting, in which the ability of the robot to change its configuration while printing will be crucial.

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Robotized Additive Manufacturing of Funicular Architectural Geometries Based on Building Materials

Cited by 18 publications

References 26 publications

An Improved Trilateral Localization Technique Fusing Extended Kalman Filter for Mobile Construction Robot

An Improved Trilateral Localization Technique Fusing Extended Kalman Filter for Mobile Construction Robot

Vision Based Trajectory Dynamic Compensation System of Industrial Robot

RAVEN: development of a novel volumetric extrusion-based system for small-scale Additive Manufacturing

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