Search Results (7)

This study introduces a digital fabrication process for producing recyclable, closed-loop wax formwork for architectural concrete applications with visually rich surface articulation while drastically reducing formwork milling time. As such, this paper presents (a) a circular large-scale production method for wax blocks via a single casting process; (b) four machine-time-optimized surface articulation strategies through CNC toolpath-driven design; (c) the investigation of different coating systems to improve architectural concrete surface quality and to ease demolding; and (d) the integration of robotic concrete shotcreting using a low-CO₂ fine-grain concrete. For the first time, wax formwork technology, characterized by its waste-free approach, has been combined with robotic shotcreting in a digital and automated workflow to fabricate fiber-reinforced, geometrically complex thin-shell concrete elements with distinct surface articulations. To evaluate the process, a series of four thin-shell concrete elements was produced, employing four distinct parametric toolpath-driven designs: linear surface articulation, crossed surface articulation, topology-adapted curve flow surface articulation, and robotic drill topology-adapted surface articulation. Results revealed a possible reduction in milling time of between 77% and 94% compared to traditional milling methods. The optimized toolpaths and design-driven milling strategies achieved a high degree of visual richness, showcasing the potential of this integrated approach for the production of high-quality architectural concrete elements. Full article

In underground coal mines, narrow and irregular tunnels, dust, and gas hazards pose significant challenges to robotic path planning, particularly for shotcrete operations. The traditional A* algorithm has the limitations of limited safety, excessive node expansion, and insufficient dynamic obstacle avoidance capabilities. To address these, a hybrid algorithm integrating adaptive A*, Q-learning, and the Dynamic Window Approach (DWA) is proposed. The A* component is enhanced through improvements to its evaluation function and node selection strategy, incorporating dynamically adjustable neighborhood sampling to improve search efficiency. Q-learning re-plans unsafe trajectories in complex environments using a redesigned reward mechanism and an adaptive exploration strategy. The DWA module facilitates real-time obstacle avoidance in dynamic scenarios by optimizing both the velocity space and the trajectory evaluation process. The simulation results indicate that the proposed algorithm reduces the number of path nodes by approximately 30%, reduces the computational time by approximately 20% on 200 × 200 grids, and increases the path length by only 10%. These results demonstrate that the proposed approach effectively balances global path optimality with local adaptability, significantly improving the safety and real-time performance in complex underground environments. Full article

The construction industry is facing a dual challenge: an increasing demand for new buildings on the one hand and the urgent need to drastically reduce emissions and waste on the other. One promising field of research to face these challenges comprises additive manufacturing (AM) technologies. Through these advanced methods, digital workflows between design and fabrication can be implemented to optimise the form and structure, unlocking new architectural freedom while ensuring sustainability and efficiency. However, to drive this transformation in construction, the new technologies must be investigated in large-scale applications. One of these fast-emerging AM techniques is Shotcrete 3D Printing (SC3DP). The present research documents the 1:1 scale manufacturing process, from digital to real, of a building section utilising SC3DP. A workflow and production steps, spanning from design over manufacturing to assembly, are introduced. The architectural design, reinforced by computational methods, was iteratively refined to adapt to manufacturing constraints. The paper also emphasises the importance of a digital twin in ensuring seamless data integration and real-time adjustments during construction. By incorporating reinforcement techniques such as short rebar insertion and robotic fibre winding, this study demonstrates the structural capabilities achievable with SC3DP. In summary, the implementation of comprehensive digital workflows utilising computational design, automated data acquisition and data flow, as well as robotic fabrication is presented to demonstrate the potential of AM methods in construction. Furthermore, this paper provides a perspective on potential future research paths and opportunities inherent in leveraging the innovative SC3DP technique. Full article

The appearance of construction defects in buildings can arise from a variety of factors, ranging from issues during the design and construction phases to problems that develop over time with the lifecycle of a building. These defects require repairs, often in the context of a significant shortage of skilled labor. In addition, such work is often physically demanding and carried out in hazardous environments. Consequently, adopting autonomous robotic systems in the construction industry becomes essential, as they can relieve labor shortages, promote safety, and enhance the quality and efficiency of repair and maintenance tasks. Hereupon, the present study introduces an end-to-end framework towards the automation of shotcreting tasks in cases where construction or repair actions are required. The proposed system can scan a construction scene using a stereo-vision camera mounted on a robotic platform, identify regions of defects, and reconstruct a 3D model of these areas. Furthermore, it automatically calculates the required 3D volumes to be constructed to treat a detected defect. To achieve all of the above-mentioned technological tools, the developed software framework employs semantic segmentation and 3D reconstruction modules based on YOLOv8m-seg, SiamMask, InfiniTAM, and RTAB-Map, respectively. In addition, the segmented 3D regions are processed by the volumetric modeling component, which determines the amount of concrete needed to fill the defects. It generates the exact 3D model that can repair the investigated defect. Finally, the precision and effectiveness of the proposed pipeline are evaluated in actual construction site scenarios, featuring reinforcement bars as defective areas. Full article

Simultaneous localization and mapping (SLAM) is the key technology for the automation of intelligent mining equipment and the digitization of the mining environment. However, the shotcrete surface and symmetrical roadway in underground coal mines make light detection and ranging (LiDAR) SLAM prone to degeneration, which leads to the failure of mobile robot localization and mapping. To address these issues, this paper proposes a robust LiDAR SLAM method which detects and compensates for the degenerated scenes by integrating LiDAR and inertial measurement unit (IMU) data. First, the disturbance model is used to detect the direction and degree of degeneration caused by insufficient line and plane feature constraints for obtaining the factor and vector of degeneration. Second, the degenerated state is divided into rotation and translation. The pose obtained by IMU pre-integration is projected to plane features and then used for local map matching to achieve two-step degenerated compensation. Finally, a globally consistent LiDAR SLAM is implemented based on sliding window factor graph optimization. The extensive experimental results show that the proposed method achieves better robustness than LeGO-LOAM and LIO-SAM. The absolute position root mean square error (RMSE) is only 0.161 m, which provides an important reference for underground autonomous localization and navigation in intelligent mining and safety inspection. Full article

Traditional reinforcement cages are manufactured in a handicraft manner and do not use the full potential of the material, nor can they map from optimised geometries. The shown research is focused on robotically-manufactured, structurally-optimised reinforcement structures which are prefabricated and can be encased by concrete through SC3DP in a combined process. Based on the reinforcement concept of “reinforcement supports concrete,” the prefabricated cages support the concrete during application in a combined AM process. To demonstrate the huge potential of combined AM processes based on the SC3DP and WAAM techniques (for example, the manufacturing of individualized CPS), the so-called FLOWall is presented here. First, the form-finding process for the FLOWall concept based on fluid dynamic simulation is explained. For this, a three-step strategy is presented, which consists of (i) the 3D modelling of the element, (ii) the force-flow analysis, and (iii) the structural validation in a computational fluid dynamics software. From the finalized design, the printing phase is divided into two steps, one for the WAAM reinforcement and one for the SC3DP wall. The final result provides a good example of efficient integration of two different printing techniques to create a new generation of freeform coastline protection structures. Full article

The research described in this paper is dedicated to the use of continuous fibers as reinforcement for additive manufacturing, particularly using Shotcrete. Composites and in particular fiber reinforced polymers (FRP) are increasingly present in concrete reinforcement. Their corrosion resistance, high tensile strength, low weight, and high flexibility offer an interesting alternative to conventional steel reinforcement, especially with respect to their use in Concrete 3D Printing. This paper presents an initial development of a dynamic robot-based manufacturing process for FRP concrete reinforcement as an innovative way to increase shape freedom and efficiency in concrete construction. The focus here is on prefabricated fiber reinforcement, which is concreted in a subsequent additive process to produce load-bearing components. After the presentation of the fabrication concept for the integration of FRP reinforcement and the state of the art, a requirements analysis regarding the mechanical bonding behavior in concrete is carried out. This is followed by a description of the development of a dynamic fiber winding process and its integration into an automated production system for individualized fiber reinforcement. Next, initial tests for the automated application of concrete by means of Shotcrete 3D Printing are carried out. In addition, an outlook describes further technical development steps and provides an outline of advanced manufacturing concepts for additive concrete manufacturing with integrated fiber reinforcement. Full article