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).

Technology has recently been developed which offers an excellent opportunity to design systems with the ability to help people in their own houses. In particular, assisting elderly people in their environments is something that can significantly improve their quality of life. However, helping elderly people outside their usual environment is also necessary, to help them to carry out daily tasks like shopping. In this paper we present a person-following shopping cart assistance robot, capable of helping elderly people to carry products in a supermarket. First of all, the paper presents a survey of related systems that perform this task, using different approaches, such as attachable modules and computer vision. After that, the paper describes in detail the proposed system and its main features. The cart uses ultrasonic sensors and radio signals to provide a simple and effective person localization and following method. Moreover, the cart can be connected to a portable device like a smartphone or tablet, thus providing ease of use to the end user. The prototype has been tested in a grocery store, while simulations have been done to analyse its scalability in larger spaces where multiple robots could coexist.

This paper reviews the source code published with the papers of a flagship robotics research conference, 2017 International Conference on Robotics and Automation (ICRA). The aim is to investigate whether the code is actually useful, i.e. can be reused by an interested reader without much effort. The interest is twofold: for one side, it makes possible to replicate and validate the results of the research; for another side, it facilitates new progress on the field, since researchers can build new systems on top of existing work. Unfortunately, reusing code is not as straightforward as it could seem, and there is a need for tools that alleviate the effort for integrating someone else's code into the own user's system. We propose the use of Docker, a Linux container technology, to turn the source code repositories into executable images, that can be run and tested locally, in an isolated environment, without the need of a costly integration with the host system.

In this paper, we present a novel boosted robot vision control algorithm. This method utilizes on-line boosting to produce a strong vision-based robot control starting from two weak algorithms. These weak methods are image-based and position-based visual servoing algorithms. The notion of weak and strong algorithms have been presented in the context of robot vision control. Appropriate error functions are defined for the weak algorithms to evaluate their suitability in the task. The integrated algorithm has superior performance both in image and Cartesian spaces. Experiments validate this claim.