Abstract:

Robotics currently plays a very important role in our daily lives and we find elements of mobile robotics in various areas of the economy and social life. Robotics also has an irreplaceable place in the educational process. The basic problem that mobile robotics must solve is the question of detecting and circumventing obstacles. At present, standard navigation systems designed for obstacle detection according to the applied principle have been narrowed down to navigation on the principle of acoustic (ultrasound), optical (infrared light), touch (contact sensors) or camera (image analysis). Modern navigation systems are based on the multi sensor principle. This means that they do not rely on just one navigation method, but combine information from multiple sensors. In our paper, we will focus on the combination of these principles of obstacle detection in computer science lessons (specifically sensing obstacles by touch, infrared distance sensor, ultrasonic distance sensor and Argos P100 Time-of-Flight Smart Camera) and their implementation using iRobot Roomba. By simulation and repeated measurements of obstacle detections, individual sensors can be compared and students can also practically verify the results. General widespread, sufficient sophistication - ie modular design and easy connection with other modules, affordability of equipment and software without complicated and lengthy development also allowed their relatively smooth implementation in the educational process. In addition, it allows students to gain practical programming experience in more than one programming language and platform.

Keywords:

Simulation, mobile robotics, educational process, obstacle detection.