Optimized Motion Control of the ViperX 300 S_ Navigating Dynamic Environments

The following research delved into optimizing the usage of a robotic arm known as ViperX 300 S with the aimof accomplishing a “pick-and-place-machine”. Furthermore, different varieties of regulator techniques andalgorithms were implemented and evaluated against each other to examine which was the most suitable for thespecific task, which is moving a fragile object. There are two algorithms developed in Python, such as thecurrent based algorithm where the robotic arm learns to reach different position with negligible error, as welleffort based where the robotic arm uses effort to reach specific positions.There is a camera on the robotic arm that was discarded, and object markers were not set or used. Regulatorswere implemented to ensure it reached its target points. The main goal was to create a model-based controland a PID regulator that was sufficient for a pick and place algorithm, which is regulating an object's movementautomatically whilst preventing harsh changes in velocity. However, due to fragile hardware and limitedprerequisite skills, this was never completed.The test area was established indoors on the plane floor with moving and stationary cardboard boxes in differentshapes, creating a maze that the robotic arm had to pass through. Simulations and measurements were carriedout to determine which were the most suitable for the task. This project contributes to injury prevention forindividuals working with robotic arms, while also advancing the implementation of algorithms that offereffective solutions with enhanced performance.