## 2 Related Work
### Algorithms and Control Systems  
Researches, such as the authors of [5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15], have developed novel algorithms and control systems that enable autonomous forklifts to navigate, plan optimal paths, avoid obstacles and efficiently perform material-handling tasks. In [5], the discussion revolves around the creation of a self-driving forklift outlining \"a system configuration using vision, laser ranger finder and sonar\". In addition, ref. [16] focuses on a closed-circuit fusion regulator for path-tracking strategies with industrial forklifts transporting substantial burdens at elevated velocities, taking into account factors like vehicle steadiness, security, skidding and convenience. In [17], [PERSON] introduced a network-oriented distributed method where system elements are linked to a \"shared CAN network\", and \"control functions\" are subdivided into minor operations that are spread across multiple microcontrollers with a restricted computational capability. The article in [10] introduces the omnidirectional setup and control method for the \"Mini Heavy Loaded Forklift Autonomous Guided Vehicle (AGV)\", designed for adaptability and agility in tight and limited spaces. [PERSON] et al. in [18] \"focused on enhancing current (AGV) flexibility in non-structured environments\". The proposed method aims to address the issue of recognizing a pallet, whose position is uncertain, by combining laser range and visual data. It also involves generating and executing smooth paths in real-time to accurately reach the desired target. Also, an important study by [PERSON] in [19] involved a thorough examination of both existing and cutting-edge radar-based object detection algorithms, including some of the most promising options from the fields of imagery and LiDAR. All tests were performed via a traditional automotive radar technique. Alongside presenting all structures, significant focus is given to the essential point cloud pre-processing for all techniques. Experimental prototypes were described early in 2010 in [20], where a multimodal framework for engaging with an independent robotic forklift was outlined. The robot employed audible and visual communication to express its present condition and planned maneuvers. The system also enables a seamless shift to manual control; when a person enters the forklift's enclosure, they can take over its operation, and the forklift remains in manual mode until the person leaves. In [21], they present an analysis that utilizes signal temporal logic (STL), which is a meticulous and unequivocal language for specifying requirements. The suggested structure assesses test cases against  
Figure 1: Summary of the content of Section 2.  
the STL formulas and utilizes \"the requirements to automatically detect test cases that do not meet the requirements\". Additionally, in [22], the authors introduced an integrated dual-sensor structure, laser and camera, and a novel algorithm named RLPF as a resolution to the issue of recognizing and localizing a pallet. A group of researchers in [23] suggested a system that can identify the pallet using object detection based on deep learning from an image, utilizing the outcomes of object detection and measurement through a horizontal 3D light detection and ranging (LiDAR) method. Furthermore, the vertical LiDAR scans the pallet for precisely adjusting the height of the fork. The system was tested in real agricultural environments. In Japan, an important work, it utilizes the findings of object identification and quantification through horizontal 3D LiDAR, where the system precisely calculates the gap between the forklift and the pallet in the outdoor area, including the distance as well as the horizontal and vertical variations. The forklift is operated using resilient Sliding Mode Control (SMC) that can handle disruptions effectively. Additionally, \"the vertical LiDAR scans the pallet\" to ensure accurate adjustment of the fork's height. [PERSON] et al. in [24] introduced a self-driving forklift (AGV) built on a forklift.