## 1 Introduction
A small robot model referred to as HPI Savage 2.1 was established, as shown in Figure 1. The vehicle is furnished with Ackermann steering and is controlled on a double track, meaning the robot can be controlled with front wheels. It is a four-wheel drive, and full control is available on each wheel to steer in any direction and control the motion. Thus, similar settings conquer as in an ordinary four-wheel-drive vehicle. It monitors that the speed and maneuverability of the robot are coupled. The robot exploits three heavy-duty direct current (DC) motors called TruckPuller3 of 7.2 V each and the controlling-model-equipped servo motor HiTec HS-5745 MG. An optical position encoder M101B of Megatron Elektronik AG & Co. is employed to drive the motor. In the era of automation, telepresence robots are becoming more attractive in various fields of medicine, academia and industries [20; 21]. Each environment has different protocols to maximize performance and minimize security threats. In [22], the authors devised methods to enhance security in IoT-enabled environments. Secure routing planning methods have been suggested by [23; 24]. The authors of [25] proposed new ideas to achieve adaptive and robust control for teleoperation. Many researchers have developed efficient mobile robot methods for the wireless sensor network in different scenarios, e.g., underwater and energy aware cluster-based schemes [26; 27; 28; 29; 30]. The list of technical parameters of auto-MERLIN is given in Table 1.  
For autonomous navigation, orientation control is crucial; otherwise, the robot cannot reach its target goal point from the start. Therefore, the main focus was to design a precise and accurate orientation controller for an approximated robot model. A cascade control loop was developed where the speed controller out is fed to the position controller. Its output serves as an input to the orientation controller. The relationship between change in orientation and the PWM controller has been established mathematically. The results shown in Section 4 present the effectiveness of the designed controller through different scenarios. There is a very small drift between the actual orientation and the desired one due to the nonlinearity of stiffness of the steering mechanism. Most mobile robots have a differential drive, so it is easier to control orientation, unlike auto-MERLIN, a car-like robot with a nonlinear steering mechanism. Orientation control of a mobile robot refers to the ability of the robot to adjust and maintain its direction of motion. This can be achieved through various techniques, such as using sensors to detect the robot's orientation, implementing feedback control algorithms to adjust the robot's motion and using mapping and localization techniques to track the robot's position and orientation. Ultimately, orientation control ensures the robot can navigate its environment and complete its intended tasks. The orientation control of a car-like mobile robot with a steering mechanism is essential to its navigation system. The robot's orientation refers to the direction in which it is facing and moving. It is important to accurately control the robot's orientation to achieve efficient and precise navigation. This article discusses the orientation control of a car-like mobile robot with a steering mechanism.