RPN (Robotic Programming Network) is an initiative to bring existing remote robot laboratories to a new dimension, by adding the flexibility and power of writing ROS code in an Internet browser and running it in the remote robot with a single click. The code is executed in the robot server at full speed, i.e. without any communication delay, and the output of the process is returned back. Built upon Robot Web Tools, RPN works out-of-the-box in any ROS-based robot or simulator. This paper presents the core functionality of RPN in the context of a web-enabled ROS system, its possibilities for remote education and training, and some experimentation with simulators and real robots in which we have integrated the tool in a Moodle environment, creating some programming courses and make it open to researchers and students (http://robotprogramming.uji.es).

The need for intervention in underwater environments has increased in recent years but there is still a long way to go before AUVs (Autonomous Underwater Vehicleswill be able to cope with really challenging missions. Nowadays, the solution adopted is mainly based on remote operated vehicle (ROV) technology. These ROVs are controlled from support vessels by using unnecessarily complex human–robot interfaces (HRI). Therefore, it is necessary to reduce the complexity of these systems to make them easier to use and to reduce the stress on the operator. In this paper, and as part of the TWIN roBOTs for the cooperative underwater intervention missions (TWINBOT) project, we present an HRI (Human-Robot Interface) module which includes virtual reality (VR) technology. In fact, this contribution is an improvement on a preliminary study in this field also carried out, by our laboratory. Hence, having made a concerted effort to improve usability, the HRI system designed for robot control tasks presented in this paper is substantially easier to use. In summary, reliability and feasibility of this HRI module have been demonstrated thanks to the usability tests, which include a very complete pilot study, and guarantee much more friendly and intuitive properties in the final HRI-developed module presented here.

Since its creation in 2014, the Robot Programming Network (RPN) has been an environment to learn and teach robotics to the general public, which has also allowed us to learn about education. In this paper, we aim to not only present the RPN and the active courses in the system but also show the evolution of this initiative in front of the changing e-learning environment and its possible future evolution towards Massive Online Open Courses (MOOCs) and cloud simulation.