## 1 Introduction  
In general, real-time simulation models based on multibody system dynamics interact with the graphical environment to illustrate the feasibility of the model and its functionality. Figure 1 shows examples of real-time simulation models and their environments, in which the environments vary from simple, see Figure 1a, to highly detailed and complex, see Figure 1d. Figure 1: Simulation models with their working environments: (**a**) Four-bar mechanism. (**b**) Material handler. (**c**) Wheel loader. (**d**) Forestry vehicle. A simulation model interacts with its environment via tires, tracks, or other bodies that it can come into contact with and moves the environmental objects; Figure 1c,d shows typical examples. Graphical software, such as Blender, and game engine software, such as Unity, Unreal Engine, and CryEngine, can be utilized to generate working environments [1; 2; 3; 4; 5]. Each software has its own advantages and disadvantages. In Unity, the C programming language is used, whereas Unreal Engine and CryEngine use the C++ language. Unity has the capability to compile games from different platforms [6], and offers preprogrammed three-dimensional models, cameras, and lights [7]. Unreal Engine is a license-free software. Graphical software makes it possible to generate environments for use in electronic games, virtual reality applications [8], and simulations. Realistic environment is an important aspect of simulations used, for example, to train operators of industrial vehicles [9; 10; 11]. Such training can help operators perform more efficiently, prevent accidents, and increase safety [12; 13; 14]. Graphical software are also widely used in the development of high-quality three-dimensional environments for educational purposes [15; 16; 17]. Photogrammetry is an estimation of the geometric and semantic properties of objects based on image analysis [18]. In other words, it is an approach used to generate three-dimensional models from detailed images of an object/area [19]. Digital photogrammetry collects data about an environment by calculating the locations of objects based on a predefined coordinate system [20]. It has been applied in many different fields and studies, such as material testing [21], recognition of deformation of beam elements and structures in fire tests [22; 23], measurement of vertical deflections in large constructions such as bridges [24], and measurement of the roughness of the soil surface for better understanding of erosion processes [25]. Researchers have also generated precise three-dimensional models of large assets such as museums and historical sites by employing photogrammetry and laser scanning approaches [26; 27; 28; 29]. Many scholars have studied how to generate 3D models using point cloud data. [PERSON] et al. introduced a methodology for the creation of 3D models. The method employs a laser scanning concept with light detection. With the help of this method, point cloud data can be collected, even in harsh weather conditions, to construct the 3D models. In addition, the collected point data can be used directly in photogrammetric software [30]. Laser scanning is widely used in building construction applications to collect point cloud data and utilise them for creation of 3D outdoor and indoor models of buildings [31]. Laser scanning has also been used to extract accurate data from rock surfaces [32]. In recent years, photogrammetry concept has also been used for mobile phones to construct 3D models of indoor places and close-range distances [33; 34]. Many studies have been conducted to increase the accuracy of the photogrammetry method in the applications of city planning and building recognition. [PERSON] et al. has introduced a procedure-based online matching to increase the accuracy of the 3D models produced with the photogrammetry. The procedure has been applied in recognizing buildings in aerial images [35]. In addition, the photogrammetry method is currently being used for constructing historical and cultural buildings [36].