Open-Source Drone Programming Course for Distance Engineering Education.

This article presents a full course for autonomous aerial robotics inside the RoboticsAcademy framework. This “drone programming” course is open-access and ready-to-use for any teacher/student to teach/learn drone programming with it for free. The students may program diverse drones on their computers without a physical presence in this course. Unmanned aerial vehicles (UAV) applications are essentially practical, as their intelligence resides in the software part. Therefore, the proposed course emphasizes drone programming through practical learning. It comprises a collection of exercises resembling drone applications in real life, such as following a road, visual landing, and people search and rescue, including their corresponding background theory. The course has been successfully taught for five years to students from several university engineering degrees. Some exercises from the course have also been validated in three aerial robotics competitions, including an international one. RoboticsAcademy is also briefly presented in the paper. It is an open framework for distance robotics learning in engineering degrees. It has been designed as a practical complement to the typical online videos of massive open online courses (MOOCs). Its educational contents are built upon robot operating system (ROS) middleware (de facto standard in robot programming), the powerful 3D Gazebo simulator, and the widely used Python programming language. Additionally, RoboticsAcademy is a suitable tool for gamified learning and online robotics competitions, as it includes several competitive exercises and automatic assessment toolspost-print5214 K

EUD-MARS: End-User Development of Model-Driven Adaptive Robotics Software Systems

Empowering end-users to program robots is becoming more significant. Introducing software engineering principles into end-user programming could improve the quality of the developed software applications. For example, model-driven development improves technology independence and adaptive systems act upon changes in their context of use. However, end-users need to apply such principles in a non-daunting manner and without incurring a steep learning curve. This paper presents EUD-MARS that aims to provide end-users with a simple approach for developing model-driven adaptive robotics software. End-users include people like hobbyists and students who are not professional programmers but are interested in programming robots. EUD-MARS supports robots like hobby drones and educational humanoids that are available for end-users. It offers a tool for software developers and another one for end-users. We evaluated EUD-MARS from three perspectives. First, we used EUD-MARS to program different types of robots and assessed its visual programming language against existing design principles. Second, we asked software developers to use EUD-MARS to configure robots and obtained their feedback on strengths and points for improvement. Third, we observed how end-users explain and develop EUD-MARS programs, and obtained their feedback mainly on understandability, ease of programming, and desirability. These evaluations yielded positive indications of EUD-MARS

New cognitive info-communication channels for human-machine interaction

The main goal of this paper is to discuss a new paradigm for robot teaching and supervising which is based on cognitive info-communication channels for human-machine interaction. According to the studied concept the robot is considered as an unskilled worker “who” (which) is strong and capable for precise manufacturing. “He” (it) has a special kind of intelligence, but “he” is handicapped in some senses, that is why “he” needs special treatment. We must command “him” clearly in a special way and we must supervise “his” work. If we can elaborate a proper way for communicating with this “new worker”, as an additional dimension of robotization, we can get a capable new “colleague”. The ultimate goal is to help the boss to be able to give the daily task to a robot in a similar way as he/she able to give the jobs to the human workers. For example, by providing the CAD documentation with some additional verbal explanation

Viewfinder: final activity report

The VIEW-FINDER project (2006-2009) is an 'Advanced Robotics' project that seeks to apply a semi-autonomous robotic system to inspect ground safety in the event of a fire. Its primary aim is to gather data (visual and chemical) in order to assist rescue personnel. A base station combines the gathered information with information retrieved from off-site sources. The project addresses key issues related to map building and reconstruction, interfacing local command information with external sources, human-robot interfaces and semi-autonomous robot navigation. The VIEW-FINDER system is a semi-autonomous; the individual robot-sensors operate autonomously within the limits of the task assigned to them, that is, they will autonomously navigate through and inspect an area. Human operators monitor their operations and send high level task requests as well as low level commands through the interface to any nodes in the entire system. The human interface has to ensure the human supervisor and human interveners are provided a reduced but good and relevant overview of the ground and the robots and human rescue workers therein

A ROS-Based Open Tool for Controlling an Educational Mobile Robot

Commercial educational robots provide an accessible entry point into the world of robotics. However, their programming is often limited to specific platforms, which can make it challenging to acquire the skills necessary for industry and research. In this study, we introduce an open-access tool developed using C++ and Arduino IDE that enables us to manage a commercial mobile robot through the Robot Operating System (ROS) middleware. This provides programmers with the ability to work in a powerful programming environment, such as Python. The robot used is the CrowBot BOLT, a kit based on ESP32 that enables wireless communication and includes various peripherals for application development. The mobile robot topics include robot velocities, RGB LEDs, a buzzer, a programmable button, and proximity, light, and line sensors. The proposal is assessed using two controllers: one for proximity and the other for tracking angular light. Both controllers are developed using Visual Studio Code. The experimental results demonstrated the proper functioning of the tool. Additionally, the response time was evaluated, and it was found that optimal performance is achieved at a frequency of 10 Hz. In summary, this proposal provides an accessible option for students and developers seeking to gain skills in robotics using ROS. The project’s repository is located at https://github.com/joseVarelaAldas/ROS-Crowbot

Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study

Developing robot agnostic software frameworks involves synthesizing the disparate fields of robotic theory and software engineering while simultaneously accounting for a large variability in hardware designs and control paradigms. As the capabilities of robotic software frameworks increase, the setup difficulty and learning curve for new users also increase. If the entry barriers for configuring and using the software on robots is too high, even the most powerful of frameworks are useless. A growing need exists in robotic software engineering to aid users in getting started with, and customizing, the software framework as necessary for particular robotic applications. In this paper a case study is presented for the best practices found for lowering the barrier of entry in the MoveIt! framework, an open-source tool for mobile manipulation in ROS, that allows users to 1) quickly get basic motion planning functionality with minimal initial setup, 2) automate its configuration and optimization, and 3) easily customize its components. A graphical interface that assists the user in configuring MoveIt! is the cornerstone of our approach, coupled with the use of an existing standardized robot model for input, automatically generated robot-specific configuration files, and a plugin-based architecture for extensibility. These best practices are summarized into a set of barrier to entry design principles applicable to other robotic software. The approaches for lowering the entry barrier are evaluated by usage statistics, a user survey, and compared against our design objectives for their effectiveness to users

A short curriculum of the robotics and technology of computer lab

Our research Lab is directed by Prof. Anton Civit. It is an interdisciplinary group of 23 researchers that carry out their teaching and researching labor at the Escuela Politécnica Superior (Higher Polytechnic School) and the Escuela de Ingeniería Informática (Computer Engineering School). The main research fields are: a) Industrial and mobile Robotics, b) Neuro-inspired processing using electronic spikes, c) Embedded and real-time systems, d) Parallel and massive processing computer architecture, d) Information Technologies for rehabilitation, handicapped and elder people, e) Web accessibility and usability In this paper, the Lab history is presented and its main publications and research projects over the last few years are summarized.Nuestro grupo de investigación está liderado por el profesor Civit. Somos un grupo multidisciplinar de 23 investigadores que realizan su labor docente e investigadora en la Escuela Politécnica Superior y en Escuela de Ingeniería Informática. Las principales líneas de investigaciones son: a) Robótica industrial y móvil. b) Procesamiento neuro-inspirado basado en pulsos electrónicos. c) Sistemas empotrados y de tiempo real. d) Arquitecturas paralelas y de procesamiento masivo. e) Tecnología de la información aplicada a la discapacidad, rehabilitación y a las personas mayores. f) Usabilidad y accesibilidad Web. En este artículo se reseña la historia del grupo y se resumen las principales publicaciones y proyectos que ha conseguido en los últimos años

SANTO: Social Aerial NavigaTion in Outdoors

In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones