Abstract
Modern industry is shifting towards flexible, advanced robotic systems to meet the increasing demand for custom-made products with low manufacturing costs and to promote a collaborative environment for humans and robots. As a consequence of this industrial revolution, some traditional, mechanical- and hardware-based safety mechanisms are discarded in favour of a safer, more dependable robot software. This work presents a case study of assessing and improving the internal quality of a European research mobile manipulator, operating in a real industrial environment, using modern static analysis tools geared for robotic software. Following an iterative approach, we managed to fix about 90% of the reported issues, resulting in code that is easier to use and maintain.

Abstract
Bin picking is a challenging problem common to many industries, whose automation will lead to great economic benefits. This paper presents a method for estimating the pose of a set of randomly arranged bent tubes, highly subject to occlusions and entanglement. The approach involves using a depth sensor to obtain a point cloud of the bin. The algorithm begins by filtering the point cloud to remove noise and segmenting it using the surface normals. Tube sections are then modeled as cylinders that are fitted into each segment using RANSAC. Finally, the sections are combined into complete tubes by adopting a greedy heuristic based on the distance between their endpoints. Experimental results with a dataset created with a Zivid sensor show that this method is able to provide estimates with high accuracy for bins with up to ten tubes. Therefore, this solution has the potential of being integrated into fully automated bin picking systems.

Abstract
To support the full adoption of Cyber-Physical Systems (CPS) in modern production lines, effective solutions need to be extended to the technological domains of robotics and industrial automation. This paper addresses the description, application and results of usage of the Open Scalable Production System (OSPS) and its underlying skill-based robot programming ideology to support machine tending of additive manufacturing operations by a mobile manipulator. © 2019, Springer Nature Switzerland AG.

Abstract
Frequently carrying high loads and performing repetitive tasks compromises the ergonomics of individuals, a recurrent scenario in hospital environments. In this paper, we design a logistic planner of a fleet of autonomous mobile robots for the automation of transporting trolleys around the hospital, which is independent of the space configuration, and robust to loss of network and deadlocks. Our robotic solution has an innovative gripping system capable of grasping and pulling non-modified standard trolleys just by coupling a plate. Robots are able to navigate autonomously, to avoid obstacles assuring the safety of operators, to identify and dock a trolley, to access charging stations and elevators, and to communicate with the latter. An interface was built allowing users to command the robots through a web server. It is shown how the proposed methodology behaves in experiments conducted at the Faculty of Engineering of the University of Porto and Braga's Hospital.

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