This paper presents a path planner for multiple unmanned aerial vehicles (UAVs) based on evolutionary algorithms (EAs) for realistic scenarios. The paths returned by the algorithm fulfill and optimize multiple criteria that 1) are calculated based on the properties of real UAVs, terrains, radars, and missiles and 2) are structured in different levels of priority according to the selected mission. The paths of all the UAVs are obtained with the multiple coordinated agents coevolution EA (MCACEA), which is a general framework that uses an EA per agent (i.e., UAV) that share their optimal solutions to coordinate the evolutions of the EAs populations using cooperation objectives. This planner works offline and online by means of recalculating parts of the original path to avoid unexpected risks while the UAV is flying. Its search space and computation time have been reduced using some special operators in the EAs. The successful results of the paths obtained in multiple scenarios, which are statistically analyzed in the paper, and tested against a simulator that incorporates complex models of the UAVs, radars, and missiles, make us believe that this planner could be used for real-flight missions.

This paper presents an open course in the University Network of Interactive Laboratories, which offers several virtual and remote laboratories on automatic control, accessible to anyone. All the details on one of these labs (a two electric coupled drives system that allows performing control practices in a 2 × 2 MIMO system with industrial applications) and the activities that can be performed with it are given. We use a low-cost solution for developing the virtual and remote labs shared in this open course, based on the use of a free authoring tool Easy Java/Javascript Simulations (EJsS) for building the laboratories' user interfaces and a cheap development platform board (BeagleBone Black). The virtual and remote labs are deployed into a free Learning Management System (Moodle) Web environment that facilitates their management and maintenance.

Web-based labs are key tools for distance education that help to illustrate scientific phenomena, which require costly or difficult-to-assemble equipment. Easy Java Simulations (EJS) is an authoring tool that speeds up the creation of these kind of labs. An excellent proof of the EJS potential is the open source physics (OSP) repository, which hosts hundreds of free EJS labs. Learning management systems, such as Moodle, provide social contexts where students interact with each other. The work described in this paper looks for the synergy of both tools, EJS and Moodle, by supporting the deployment of EJS labs into Moodle and thus enriching them with social features (e.g., chat, forums, and videoconference). To test this approach, the authors have created the ball and beam lab, which helps students of automatic control engineering to train different advanced techniques (robust, fuzzy, and reset control), and compare their performance in relation to a conventional proportional-integral-derivative control.