This paper presents a method on how to compute the position of a robotic arm in the 2D and 3D spaces. This method is slightly different from the well-known methods, such as forward or inverse kinematics. The method presented in this paper is an optical method, which uses two video cameras in stereo vision configuration to locate and compute the next move of a robotic arm in space. The method recognizes the coordinates of the markers placed at the joints of the robotic arm using the two video cameras. The coordinate points of these markers are connected with straight lines. Around certain points, circles are drawn. From the tangent to the circles, a non-Cartesian (orthogonal) coordinate system is drawn, which is enough to compute the target position of the robotic arm. All of these drawings are overlaid on the live video feed. This paper also presents another method for calculating the stereo distance using the triangulation method. An alternative method is also presented when a non-Cartesian (orthogonal) 3D coordinate system is created, which is used to compute the target position of the robotic arm in the 3D space. Because the system is in a loop, it can make micro-adjustments of the robotic arm, in order to be exactly in the desired position. In this way, there is no need to make calibrations for the robotic arm. In an industrial system, there is no need to stop the production line, which can be a really big cost saver.

The aim of this paper is to present the genetic algorithm used in programming a solar tracker robot. The solar tracker robot can be used to increase the efficiency of solar panels by rotating them toward the Sun. When the efficiency of solar panels is increased, they can reduce the space occupied by them. Efficiency can also be increased by genetic algorithms, where a solar panel can evolve and thus track the Sun more precisely. The genetic algorithm implemented in the solar tracker is the main focus of this paper. The genetic algorithm is presented with a flow chart and formulas. After this, the system is implemented on a solar tracker robot and validated with real experiments. The solar tracker robot algorithm is implemented in the C language on a microcontroller built on an FPGA platform.

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