A low-cost table-top robot platform for measurement science education in robotics and artificial intelligence

Abstract

Robotics and artificial intelligence represent highly interdisciplinary fields, which - in particular on the bachelor level - makes providing a strong fundamental background in the education challenging. With respect to lab exercises in measurement, one approach to provide interdisciplinary hands-on experience is to embed experiments for measurement science in a robotic context. We present a low-cost robot platform that can be used to address several measurement science and sensor topics, and also other aspects such as machine learning, actuators and mechanics. The 3D printed chassis can be equipped with different sensors for environment perception but also be adapted to different embedded PC platforms. In order to also introduce concepts of robot simulation and realization approaches in a hands-on fashion, the table-top robot is also available as a digital twin in the simulation environments Gazebo and CoppeliaSim®, where, e.g., limitations of simulations and required adaption of models to consider non ideal effects of sensors can be studied.