Abstract
The European Project Semester (EPS) is a multicultural and multidisciplinary project-based learning semester offered by a network of providers, including the Instituto Superior de Engenharia do Porto (ISEP). In the spring of 2020/2021, five EPS@ISEP students from different areas of studies and countries - Portugal, Romania, Poland and France - teamed up. Given the disorganization and overcrowding affecting the experience of attendees at large events, the team decided to create a Crowd Orchestration solution for large outdoor festivals. To this end, the team designed ScanGo with real time alerts about the number of people in predefined areas, suggestion of alternative activities within the event or indication of the best route to go from one stage to the another. This way, ScanGo also intends to minimize the effects of the undergoing pandemic, allowing people to safely experience open air festivals. This paper reports the different stages of the teamwork, encompassing the preliminary studies and the design of ScanGo, followed by the development and test of a proof of concept prototype.

Abstract

Abstract
Continuous Integration and Deployment in the robotics domain is still underutilized when compared to other fields of software development. Also, conventional testing techniques used in CI/CD pipelines are usually not enough to fully test a robotic project in its integrity. In this paper, an analysis is made regarding the usage of CI/CD techniques in robotic related repositories to both verify the veracity of these statements, as well as finding their causes. Additionally, a novel approach in the scope of CI/CD is explored, making use of cloud-based technologies to add additional automated simulation tests to the pipeline and integrate them with ease in the development of robotic software. Finally, the proposed approach is showcased in an industrial application. © 2021 IEEE.

Abstract
There are significant difficulties in deploying and reusing application code within the robotics community. Container technology proves to be a viable solution for such problems, as containers isolate application code and all its dependencies from the surrounding computational environment. They are also light, fast and performant. Manual generation of configuration files required by orchestration tools such as Docker Compose is very time-consuming, especially for more complex scenarios. In this paper a solution is presented to ease the development and deployment of Robot Operating System (ROS) packages using containers, by automatically generating all files used by Docker Compose to both containerize and orchestrate multiple ROS workspaces, supporting multiple ROS distributions and multi-robot scenarios. The proposed solution also generates Dockerfiles and is capable of building new Docker images at run-time, given a list of desired ROS packages to be containerized. Integration with existing Docker images is supported, even if non-ROS-related. After an analysis of existing solutions and techniques for containerizing ROS nodes, the multi-stage pipeline adopted by the proposed solution for file generation is detailed. Then, a real usage example of the proposed tool is presented, showcasing how it an aid both the development and deployment of new ROS packages and features. © 2021 IEEE.

Abstract
This paper addresses the concept of Industry 4.0 from the perspective of the molds industry, a key industry in today's industrial panorama. With its constant modernization, several technologies have been introduced, in particular regarding machining equipment. With each brand and model requiring different (proprietary) interfaces and communication protocols, this technological diversity renders the automatic interconnection with production management software extremely challenging. In this paper a methodology to build monitoring solutions for machining devices is defined, based on the main equipment and operations used by molds industry companies. For a standardized approach, OPC UA is used for high-level communication between the various systems. As a key result of this paper, and given the variety of monitoring systems and communication protocols, the developed approach combines various different machine interfaces on a single system, in order to cover a relevant subset of machining equipment currently in use by the molds industry. This kind of all-in-one approach will give production managers access to the information needed for a continuous monitoring and improvement of the entire production process. (C) 2021 The Authors. Published by Elsevier B.V.

Abstract
Although advances have been made in reducing the time needed for manhole inspection, the procedure is still mostly done manually, with workers having to enter and visually assess the areas being inspected. There is also a growing need to have these structures inspected regularly, in order to prevent casualties and services interruption, as well as the higher cost of rebuilding instead of repairing these structures, which is possible only if pathologies are identified at early stages. This situation renders the task a good target for automation. This paper reviews a set of existing manhole, tunnel and duct inspection systems to ascertain the main features required for the task, as well as the technologies currently used. Most of the present-day solutions are rather expensive and cumbersome, requiring the deployment of relatively heavy equipment and specialized personnel to operate them. With the recent development of laser range sensors and depth (RGBD) cameras with small form factors and weights, the development of solutions with higher portability and lower cost become feasible. Such a solution could improve considerably the rate at which manholes are inspected, and the technology could be used to generate textured models to be analyzed and reported by a remotely located specialist, both online and offline. The work presented here lays the ground for the development of such a system in our research group who has been working on low-cost systems for the generation of 3D textured models for automated inspection. © 2021, Springer Nature Switzerland AG.