Udział w międzynarodowych konkursach robotycznych jako nowa forma podróży studenckich

W artykule przedstawiono możliwości odbywania podróży zagranicznych przez studentów uczestniczących w międzynarodowych konkursach, w szczególności w zawodach robotycznych, popularnych między innymi wśród polskich studentów. Jak pokazują zebrane dane zawody te przyciągnęły nawet kilka tysięcy uczestników w ciągu ostatnich lat. Zaprezentowany został dodatkowy efekt ich uczestnictwa w konkursach, jakim jest turystyka uprawiana w trakcie takich wyjazdów i nazwana przez autorów turystyką konkursową

Participation in international robotics competitions as a new form of student travel

The article presents opportunities for foreign travel by students based on trips to international competitions, in particular robotic competitions. As the data collected show, these have attracted several thousand participants in recent years. The article presents an additional effect of participation in such competitions which is tourism during the trips

Using LabVIEW and ros for planning and coordination of robot missions, the example of ERL emergency robots and university rover challenge competitions

The article presents the main functionalities and principles for operating a software for multi-robotic mission coordination developed for competitions ERL Emergency Robots 2017, as well as its adaptation during University Rover Challenge. We have started with an overview of similar software used in commercial applications or developed by other research groups. Then, our solution is thoroughly described, with its user interface made in LabVIEW and the communication layer based on ROS software. Two cases of robotic competitions proved our software to be useful both for planning and for managing the mission. The system supports the operator in teleoperation and during partial autonomy of the robots. It offers reporting on the robots’ positions, Points of Interest (POI), tasks status. Reports are generated in KML/KMZ formats, and allow us to replay the mission, and analyze it

Machine Learning in Creating Energy Consumption Model for UAV

The growing interest in the utilization of Unmanned Aerial Vehicles (UAVs) demands minimizing the costs of robot maintenance, where one of the main aspects relates to energy consumption. This manuscript presents a novel approach to create an energy consumption model for UAVs. The authors prove, based on experimentally collected data using a drone carrying various payloads, that Machine Learning (ML) algorithms allow to sufficiently accurately estimate a power signal. As opposed to the classical approach with mathematical modeling, the presented method does not require any knowledge about the drone’s construction, thus making it a universal tool. Calculated metrics show the Decision Tree is the most suitable algorithm among eight different ML methods due to its high energy prediction accuracy of at least 97.5% and a short learning time which was equal to 2 ms for the largest dataset

Machine Learning in Creating Energy Consumption Model for UAV

The growing interest in the utilization of Unmanned Aerial Vehicles (UAVs) demands minimizing the costs of robot maintenance, where one of the main aspects relates to energy consumption. This manuscript presents a novel approach to create an energy consumption model for UAVs. The authors prove, based on experimentally collected data using a drone carrying various payloads, that Machine Learning (ML) algorithms allow to sufficiently accurately estimate a power signal. As opposed to the classical approach with mathematical modeling, the presented method does not require any knowledge about the drone’s construction, thus making it a universal tool. Calculated metrics show the Decision Tree is the most suitable algorithm among eight different ML methods due to its high energy prediction accuracy of at least 97.5% and a short learning time which was equal to 2 ms for the largest dataset