Rafael Lírio Arrais

Abstract
Several approaches with interesting results have been proposed over the years for robot grasp planning. However, the industry suffers from the lack of an intuitive and reliable system able to automatically estimate grasp poses while also allowing the integration of grasp information from the accumulated knowledge of the end user. In the presented paper it is proposed a non-object-agnostic grasping pipeline motivated by picking use cases from the aerospace industry. The planning system extends the functionality of the simulated annealing optimization algorithm for allowing its application within an industrial use case. Therefore, this paper addresses the first step of the design of a reconfigurable and modular grasping pipeline. The key idea is the creation of an intuitive and functional grasping framework for being used by factory floor operators according to the task demands. This software pipeline is capable of generating grasp solutions in an offline phase, and later on, in the robot operation phase, can choose the best grasp pose by taking into consideration a set of heuristics that try to achieve a successful grasp while also requiring the least effort for the robotic arm. The results are presented in a simulated and a real factory environment, relying on a mobile platform developed for intralogistic tasks. With this architecture, new state-of-art methodologies can be integrated in the future for growing the grasping pipeline and make it more robust and applicable to a wider range of use cases.

Abstract
For remaining competitive in the current industrial manufacturing markets, coating companies need to implement flexible production systems for dealing with mass customization and mass production workflows. The introduction of robotic manipulators capable of mimicking with accuracy the motions executed by highly skilled technicians is an important factor in enabling coating companies to cope with high customization. However, there are some limitations associated with the usage of a fully automated system for coating applications, especially when considering customized products of large dimensions and complex geometry. This paper addresses the development of a collaborative coating cell to increase the flexibility and efficiency of coating processes. The robot trajectory is taught with an intuitive programming by demonstration system, in which an icosahedron marker with multicoloured LEDs is attached to the coating tool for tracking its trajectories using a stereoscopic vision system. For avoiding the construction of fixtures and allowing the operator to freely place products within the coating work cell, a modular 3D perception system was developed, relying on principal component analysis for performing the initial point cloud alignment and on the iterative closest point algorithm for 6 DoF pose estimation. Furthermore, to enable safe and intuitive human-robot collaboration, a non-intrusive zone monitoring safety system was employed to track the position of the operator in the cell.

Abstract
The Real-Time Monitoring and Performance Management suite tool, known as UIL (User Interface Layer), was developed in the FASTEN project, a R&D initiative financed by the innovation and research program H2020 within a bilateral Europe-Brazil call. UIL was conceived and deployed in the IIoT architecture of the project. The goal was to provide a usercentered assistance to the human operator for both decision-responsibility and control loop, in a continuously updating information fashion, related to system's state. In order to have experimental results, a qualitative assessment was conducted in an industrial environment. The architecture proposed was based on the adoption of a Knowledge Engineering User Interface to support Operator 4.0. Our empirical experiments point out to a successful set of results. Copyright (C) 2021 The Authors.

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.