Developments in the automation of construction processes, observable in recent years, is focused on speeding up the construction of buildings and structures. Additive manufacturing using concrete mixes are among the most promising technologies in this respect. 3D concrete printing allows the building up of structure by extruding a mix layer by layer. However, the mix initially has low capacity to transfer loads, which can be particularly troublesome in cases of external components that need to be placed on top such as precast lintels or floor beams. This article describes the application of additive manufacturing technology in the fabrication of a building wall model, in which the door opening was finished with automatic lintel installation. The research adjusts the wall design and printing process, accounting for the rheological and mechanical properties of the fresh concrete, as well as design requirements of Eurocode. The article demonstrates that the process can be planned precisely and how the growth of stress in fresh concrete can be simulated, against the strength level developed. The conclusions drawn from this research will be of use in designing larger civil structures. Furthermore, the adverse effects of concrete shrinkage on structures is also presented, together with appropriate methods of control.

Research on the development of control systems for loader cranes, despite their importance in the industry, is conducted by only a few scientific centers. West Pomeranian University of Technology, Szczecin in collaboration with loader cranes manufacturer - Cargotec company, started research on the multisensory monitoring system for cranes. proposed system also allows you to track the position of the operator. This paper presents the subsystem for ground plane estimation and ground points filtration. The developed algorithm uses data from the Velo dyne LIDAR VLP-16 scanner. The subsystem is designed for real time operation. It is based on the RANSAC algorithm and vector dot product. The effectiveness of the algorithm was compared with other algorithms described in this publication. Tests were carried out on a loader crane test bench at various positions of the LIDAR sensor. Experiments confirms that ground plane estimation results of the proposed algorithm are better than other presented methods.

The segmentation and analysis of the environment using three-dimensional (3D) data (point clouds) is a dynamically developing area. This article presents a real-time ground filtration method for the loader crane environment monitoring system. The falling prices of depth sensors based on light detection and ranging (LIDAR), time of flight (ToF), radio detection and ranging (RADAR) technologies, and growth-computing power led us to use the Velodyne VLP-16 sensor in the developed system. In the presented filtering solution, we use characteristic scan pattern properties, the dot product of vectors, and interpolation using the RANSAC method. Algorithm performance was evaluated based on real data acquired under different conditions, and the results were compared to known filtration methods. The described algorithm is developed for real-time operation; therefore, the computation time is critical. Furthermore, in this article, we discuss other methods used to extract ground points from the entire point cloud in real time, describe Velodyne VLP-16 scanner and data acquisition methods.