## 1 Introduction  
The most common serial manipulator design in the industry benefits from its so-called angular structure with 6 degrees of freedom, which can easily reach the surrounding areas and achieve multiple different poses. However, this universal kinematic structure has a disadvantage in that when such robots are deployed in densely built workplaces, they can collide either with obstacles or themselves. Custom manipulator designs can overcome this problem, as best shown in the work by [PERSON] [1], where he presented a robotic manipulator with a task-desired kinematic structure. Evolutionary robotics (ER) is often used to create custom robots or their components, such as the morphology, kinematics, or controllers. It is a set of evolutionary techniques used for the development of robotic systems, as stated by [PERSON] [2] in his book, which delivered the theoretical basics for this topic. ER strategies were described in a survey by [PERSON] [3] and in a newer paper by [PERSON] [4]. ER is often used to synthesize robot controllers for a specific behavior [5] or multiple behaviors [6]. One of the use cases for evolutionary robotics is in determining the kinematics required for a robot to optimally perform a task or a set of tasks. The reason for the usage of optimization algorithms is that the synthesis of the kinematic structure of a manipulator is a rather complicated task if an analytical approach is used. One of the recent achievements in terms of analytical manipulator synthesis was the synthesis of three-revolute spatial chain by [PERSON] to allow five poses [7]. Evolutionary robotics can provide satisfying results nowadays, allowing more degrees of freedom and more poses (or even entire trajectories). The optimization problem is often carried out on kinematic structures built from predefined modules. [PERSON] [8] was one of the first that demonstrated the possible application of evolutionary robotics in practical engineering work by evolving a design for walking robots. More of these examples can be found in the survey by [PERSON] [9]. The research on the evolution of manipulators built from adaptive modules to perform desired tasks was started by [PERSON] [10], who determined the optimal robot configuration and the length of links between modules. [PERSON] [11] also found the optimal kinematic structure for the modules that he defined. Another solution was presented by [PERSON] et al. [12; 13], who presented a more developed approach with so-called pseudo-joints, which with the use of a genetic algorithm (GA) attempts to find the kinematic structure with the best manipulability. Their outcomes were later verified by [PERSON] [14] in an experiment with a real manipulator. It is important to note that the use of a genetic algorithm is not the only possible approach to solve the presented issue. [PERSON] [15] used a simulated annealing algorithm, while [PERSON] [16] addressed the issue using a heuristic-guided tree search algorithm. [PERSON] [17] and [PERSON] [18] applied a deterministic quasi-Newton algorithm to find the local minimum of a cost function. The complexity of the modules from which a robot is constructed determines the optimization difficulty. In this context, the complexity of a module can be thought of as a number of parameters describing one module and the variety of shapes it can achieve. [PERSON] et al. [19] showed that changing the number and position of connecting faces in a module influences the evolvability of a modular robot. In another study [20], [PERSON] and [PERSON] used the same robotic modules to show how changing the length of modules affects the resulting robot structures and performance. The performance of an open-chain manipulator can be improved for a specific task by optimizing the Denawit-Hartenberg (DH) [21] parameters. [PERSON] optimized the DH parameters of a 3R manipulator for a specific workspace geometry [22]. [PERSON] [23] presented a method for synthesizing serial redundant manipulators by optimizing their DH parameters in an environment with obstacles.