## 1 Introduction
This allows maintenance workers to gather debugging data quickly, update configurations or simply visualize the production process, which can be carried out using SCADA (supervisory control and data acquisition)/ HMI (human-machine interface) hardware and software [10; 11]. However, it should be noted that the complex structure and high prices of such systems can reduce the number of potential implementations. Moreover, nowadays, the idea of the Internet of Things becomes an inseparable part of modern control systems. When it comes to robotic constructions, there is a massive need to equip the robots with a smart control module. Modern control units may also be determined by additional requirements, e.g., shock resistance and compact size. These features involve the need to create a dedicated embedded system, which combines real-time operations with constant online access ensured by the IoT. These embedded systems may also apply artificial intelligence algorithms to gather environmental data (e.g., example neural networks for sensor signal analysis and deep learning vision systems) and for control. The solution proposed in the paper is low-cost and consists of a single module that is able to host an HMI service while controlling the operation of the machinery. If the HMI is published as an interactive website (accessible using any web browser), no additional software is required. The design process of the complex control structures and mechanisms requires complicated calculations. In the case of geometrical synthesis, the model of the kinematic chain is rather simple. However, the solution to the problem of providing the desired operation requires a complex search of possible solutions. This can be carried out using the naive, monotonous brute force method or, as it has already been proven [12], the optimization algorithm can be applied to solve the problem more effectively. The catalogue of metaheuristic algorithms is evolving and expanding unceasingly. The swarm intelligence methods are the most popular techniques among nature-inspired metaheuristic algorithms. Their successful applications in different disciplines have already been described and published, and include:  
* Economic issues [13];
* Design of electronic devices [14];
* Material strength [15];
* Optimization of electrical machines [16];
* IT network support [17];
* Management of power systems [18; 19];
* Medicine [20];
* And many others. The paper describes the design process of a wheel-legged robot. It is divided into thematically established sections that provide subsequent steps and subjects of the design. The introduction is followed by a state-of-the-art discussion. It establishes the background for the considerations presented in the next parts of the paper. At the beginning, the embedded microcontroller system is described. In this section, the chosen motors are briefly characterized and the applied control structures are also discussed. The following section provides the description of the most important mechanism of the wheel-legged robot. It puts a special focus on the novel approach of geometrical synthesis of the robot's suspension. The requirements and the constraints for the kinematic chain are provided in this part of the manuscript. Then, the flower pollination algorithm is briefly described and its application to calculate the dimensions of the four-bar linkage suspension (to fulfill defined requirements) is described in detail. The description of the swarm intelligence-based optimization process is supported with chosen simulations results and the real prototype of the wheel-legged robot. In the same section, the second application of the FPA is also briefly presented. The speed controller used for the BLDC motors is optimized with the same algorithm that is used in the synthesis of the mechanical system. This part of the paper summarizes the speed transients achieved with the robot prototype. The next section of the article is focused on the master controller--ESP32--and the developed HMI system.