## 2 Literature Review
There are techniques for navigating an automated guided vehicle in two different environments to reach a goal. These environments are as follows: (a) normal (unguided) and (b) guided. An artificial potential function is defined to find the target in the normal environment. Conducting initial computation of the optimal path from several paths, from the source to the destination, and pre-pathing the selected path through the nodes (radio frequency identification tags) is the technique for the controlled environment. The bottlenecks prevent the desired movement in both environments [12]. The self-localisation of a mobile robot is always a key aspect of the autonomous navigation task. The challenge of self-localisation becomes more complicated when the robot has sensors with low levels of precision and accuracy. These works [13,14] confront this aspect by finding a solution using the soft sensor paradigm. The deployment of autonomous trucks in warehouses and the automotive industry is elaborated in [15], where the authors build on the scientific project \"Ex-Coherence Centre for Intelligent Transport Systems\", aimed at proposing a methodology to calculate the necessary number of autonomous trucks and trucks deployed in logistics warehouses. The methodology is based on the requirement that autonomous trucks should have no downtime. To achieve such an objective, the internal dynamics of the discrete events of these systems should be considered when deriving the model to be used for simulation, analysis, optimisation, and control. Among the various discrete event models, Petri nets (PNs) are particularly effective due to several relevant properties. In addition, several high-level PN models (e.g., colour, continuous, or hybrid) allow for solving complex and high-dimensional problems that typically arise from real-world applications in logistics and freight transportation systems [16,17]. The independence of static reading systems is a subject of current automated guided vehicles research. While variations of the guidance principle based on inductive or optical effects have been the predominant navigation techniques for decades, currently laser triangulation can be considered as the standard. To create a laser-based navigation system, the environment must be equipped with reflective markers. To overcome this drawback, a vision-based navigation system is currently being developed at PSLT. With this new technology, it will be possible to create an automated guided vehicle without any prior preparation of the environment [18]. Automated guided vehicles are ideal for use in repetitive flow applications. After identifying the flows where automation will create the most added value for the company, the path to automation is gradually created. Once it is identified which flows need to be automated, lean thinking is used to eliminate waste and standardise the process for maximum efficiency [19]. Trends in different markets, and thus the development of automated guided vehicle manufacturers, are also extremely important for customers' investment decisions. Customers need to make sure that the technology being procured is future-oriented and that the manufacturer will be available in the automated guided vehicles market segment in the long run. The selected automated guided vehicles manufacturer should be available for service and support of the system as well as for spare parts supply in the long term [20]. Automated guided vehicles are often implemented in cross-industry environments, especially in manufacturing centres that use working methods such as lean manufacturing or just-in-time [21]. This is because this transportation solution covers the distance between the warehouse and the production centre and delivers raw materials to the production lines. However, in facilities with a larger number of orders, automated guided vehicles may not meet the logistics needs of the warehouse because these machines have limited carrying capacity.