The proliferation of new data-intensive applications in asymmetric communication environments has led to an increasing interest in the development of push-based techniques, in which the information is broadcast to a large population of clients in order to achieve the most efficient use of the limited server and communication resources. It is important to note that quite often the data that is broadcast is time-critical in nature. Most of the related current research focuses on a pure push-based approach (Broadcast Disks model), where the transmission of data is done without allowing explicit requests from the users. More recently, some bidirectional models incorporating a low-capacity uplink channel have been proposed in order to increase the functionality of the Broadcast Disks model. However, the impact of integration of the uplink channel has been investigated using only static client profiles or ignoring the existence of time-sensitive data. None of the existing models integrates all the characteristics needed to perform effectively in a real-world, dynamic time-critical asymmetric communication environment. In this paper we present an adaptive data dissemination model and the associated on-line scheduling algorithms. These improve the functionality and performance of bidirectional broadcast models, maximizing the total number of satisfied users in asymmetric communication environments with dynamic client profiles and time requirements (e.g., mobile systems). This is achieved by means of dynamic adaptation of the broadcast program to the needs of the users, taking into account the bandwidth constraints inherent in asymmetric communication environments and the deadline requirements of the user requests. Performance is evaluated by simulation of a real-time asymmetric communication environment.

This paper presents an open-access platform for practical learning of intelligent robotics in engineering degrees: Robotics-Academy. It comprises a collection of exercises including recent service robot applications in real life, with different robots such as autonomous cars, drones or vacuum cleaners. It uses Robot Operating System (ROS) middleware, the de facto standard in robot programming, the 3D Gazebo simulator and the Python programming language. For each exercise, a software template has been developed, performing all the auxiliary tasks such as the graphical interface, connection to the sensors and actuators, timing of the code, etc. This also hosts the student’s code. Using this template, the student just focuses on the robot intelligence (for instance, perception and control algorithms) without wasting time on auxiliary details which have little educational value. The templates are coded as ROS nodes or as Jupyter Notebooks ready to use in the web browser. Reference solutions for illustrative purposes and automatic assessment tools for gamification have also been developed. An introductory course to intelligent robotics has been elaborated and its contents are available and ready to use at Robotics-Academy, including reactive behaviors, path planning, local/global navigation, and self-localization algorithms. Robotics-Academy provides a valuable complement to master classes in blended learning, massive online open courses (MOOCs) and online video courses, devoted to addressing theoretical content. This open educational tool connects that theory with practical robot applications and is suitable to be used in distance education. Robotics-Academy has been successfully used in several subjects on undergraduate and master’s degree engineering courses, in addition to a pre-university pilot course.

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 tools.

The proliferation of new data-intensive applications in asymmetric communication environments has led to an increasing interest in the development of push-based techniques, in which the information is broadcast to a large population of clients in order to achieve the most efficient use of the limited server and communication resources. It is important to note that quite often the data that is broadcast is time-critical in nature. Most of the related current research focuses on a pure push-based approach (Broadcast Disks model), where the transmission of data is done without allowing explicit requests from the users. More recently, some bidirectional models incorporating a low-capacity uplink channel have been proposed in order to increase the functionality of the Broadcast Disks model. However, the impact of integration of the uplink channel has been investigated using only static client profiles or ignoring the existence of time-sensitive data. None of the existing models integrates all the characteristics needed to perform effectively in a real-world, dynamic time-critical asymmetric communication environment. In this paper we present an adaptive data dissemination model and the associated on-line scheduling algorithms. These improve the functionality and performance of bidirectional broadcast models, maximizing the total number of satisfied users in asymmetric communication environments with dynamic client profiles and time requirements (e.g., mobile systems). This is achieved by means of dynamic adaptation of the broadcast program to the needs of the users, taking into account the bandwidth constraints inherent in asymmetric communication environments and the deadline requirements of the user requests. Performance is evaluated by simulation of a real-time asymmetric communication environment.

Reconfigurable computing provides a paradigm to create intelligent systems different from the classic software computing approach. Instead of using a processor with an instruction set, a full stack of middleware, and an application program running on top, the field-programmable gate arrays (FPGAs) integrate a cell set that can be configured in different ways. A few vendors have dominated this market with their proprietary tools, hardware devices, and boards, resulting in fragmented ecosystems with few standards and little interoperation. However, a new and complete toolchain for FPGAs with its associated open tools has recently emerged from the open-source community. Robotics is an expanding application field that may definitely benefit from this revolution, as fast speed and low power consumption are usual requirements. This paper hypothesizes that basic reactive robot behaviors may be easily designed following the reconfigurable computing approach and the state-of-the-art open FPGA toolchain. They provide new abstractions such as circuit blocks and wires for building intelligent robots. Visual programming and block libraries make such development painless and reliable. As experimental validation, two reactive behaviors have been created in a real robot involving common sensors, actuators, and in-between logic. They have been also implemented using classic software programming for comparison purposes. Results are discussed and show that the development of reactive robot behaviors using reconfigurable computing and open tools is feasible, also achieving a high degree of simplicity and reusability, and benefiting from FPGAs’ low power consumption and time-critical responsiveness.