Multipurpose Robot Arm

Sammanfattning: Today’s society is facing a large increase of automation and smart devices. Everything from coffee machines to fridges include some kind of electronics and embedded systems. The focus of this Bachelor’s thesis was to dive deeper into how these automated devices can be controlled and more specifically a robot arm. The main purpose revolved around constructing a robotic arm that could be controlled through three different methods using MATLAB. These three were manual control, numerical analysis control and with a neural network based control. The prototype was created by assembling six servo motors onto 3D-printed parts. The arm consisted of three main parts which were a base, an arm and a gripper. The system was controlled by an Arduino micro-controller connected to a computer. The results show that the manual control method was easy to implement, fast and reliable. It allows control of all the angels for each servo motor, which also means controlling each individual degree of freedom. The numerical way, using Newton-Raphson’s method, broadened the abilities to control the arm but was slower. The third and final solution was to use fuzzy-logic. This ended up being a powerful method allowing for great control with low latency. While unreliable, the method showed great potential and with refinement could surpass the others. The conclusion was that the neural network method was the overall best method for controlling and manoeuvring the robot arm using MATLAB.