*Proceeding Paper* **Developing a Simulation Model for Autonomous Driving Education in the Robobo SmartCity Framework †**

**Daniel Juanatey, Martin Naya, Tamara Baamonde and Francisco Bellas \***

GII, CITIC Research Center, Campus de Elviña, 15008 A Coruña, Spain; daniel.juanatey@udc.es (D.J.); martin.naya@udc.es (M.N.); tamara.bardao@udc.es (T.B.)

**\*** Correspondence: francisco.bellas@udc.es

† Presented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.

**Abstract:** This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the smartphone-based robot Robobo and a real model of a smart city. We describe the development of a simulation model of Robobo SmartCity in the CoppeliaSim 3D simulator, implementing both the real mock-up and the model of Robobo. In addition, a set of Python libraries that allow teachers and students to use state-of-the-art algorithms in their education projects is described too.

**Keywords:** intelligent robotics; educational robots; self-driving cars; robotic simulation; computer vision

### **1. Introduction**

This work is focused on an educational framework for teaching intelligent robotics in secondary school or university, developed at the University of Coruña: the Robobo SmartCity. This framework is based on two main elements: (1) the smartphone-based robot Robobo [1], and a (2) model of a smart city, considering both simulation-based and real formats. In this framework, many different challenges and lessons on intelligent robotics can be carried out, mainly focused on the field of self-driving vehicles. It allows teachers to propose challenges dealing with basic problems in robotics, such as control navigation and obstacle avoidance, but also more complex ones that require computer vision, such as traffic sign detection and object identification. The idea of using autonomous driving and smart cities as environments for robotics teaching is becoming quite popular. For example, the authors of [2] proposed a modular and integrated approach towards teaching autonomous driving. Another relevant approach is the autoauto platform [3], which utilizes the concept of self-driving cars for teaching robotics and AI to young students. Costa et al. [4] presented an autonomous driving simulator to gain the attention of and prepare the students to compete in the Portuguese National Robotic Festival (PNRT), especially in the Autonomous Driving Competition (ADC). A very similar approach to the one proposed here is Duckietown [5], an online MOOC for teaching AI and robotics based on self-driving cars, with which the authors have created a whole educational environment, with different city layouts, traffic signals, etc.
