Abstract
Visual inspection based systems are important tools to ensure the quality of manufactured parts in industry. This work presents an automatic visual inspection approach for defect detection in turbo vanes in the investment casting industry. The proposed method uses RANSAC for robust line and circle detection to extract relevant information to discriminate between a good part and a defected one. Then, using this data a feature vector is created serving as input to a SVM classifier that after the training phase is able to discriminate and classify between a good sample or not. To test the proposed approach a private database was created containing 650 turbo vanes (which gives 2600 different samples to train and test). On this database the proposed method achieved an average accuracy of 99.96%, an average false negative rate of 0.00% and an average false positive rate of 0.05%, using a 5-fold cross validation protocol, which demonstrates the success of the proposed method. Moreover, the proposed image processing pipeline was deployed into Raspberry Pi 4 Model B part of a visual inspection machine, and is working daily at ZCP-Zollern and Comandita Portugal, which proves the method's robustness. © 2020 Owner/Author.

Abstract
Throughout this paper, the model, its parameter estimation and a controller for a solution using a DC motor with a gearbox worm, coupled to a non-rigid joint, will be presented. First, the modeling of a non-linear system based on a DC Motor with Worm Gearbox coupled to a non-rigid joint is presented. The full system was modeled based on the modeling of two sub-systems that compose it—a non-rigid joint configuration and the DC motor with the worm gearbox configuration. Despite the subsystems are interdependent, its modelling can be performed independently trough a carefully chosen set of experiments. Modeling accurately the system is crucial in order to simulate and know the expected performance. The estimation process and the proposed experimental setup are presented. This setup collects data from an absolute encoder, a load cell, voltage and current sensors. The data obtained from these sensors is presented and used to obtaining some physical parameters from both systems. Finally, through an optimization process, the remaining parameters are estimated, thus obtaining a realistic model of the complete system. Finally, the controller setup is presented and the results obtained are also presented. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Abstract
Ultrasonic sensors offers attractive features at an affordable cost. The main problem faced by the use of these devices is that the data obtained are not so easy to interpret, restricting their efficiency. This paper describes a binaural sensor system that is able to determine the coordinates of an object or a target in a two-dimensional space, focusing on mathematical and signal processing techniques to provide accurate measurements and increase the system reliability. The proposed work consists only of low cost components, which aims to demonstrate that improvement is possible. Experimental tests, performed in different scenarios, reported good accuracy and repeatability of the measurements.

Abstract
The Robot@Factory Lite (R@FL) is a competition held at the Portuguese Robotics Open that aims to present a problem inspired by the deployment of autonomous mobile robots on a factory shop floor. This paper proposes an approach to transform this competition according to the Industry 4.0 concept using the Wi-Fi to attribute orders to the mobile robot. The main contribution of this paper is to address a Supply Chain Management (SPM) of the ERP (Enterprise Resource Planning) that will inform the tasks to the robot so that it can schedule. It is presented a new hardware architecture that should be able to read the information of the parts through Wi-Fi in a client-server methodology. It also includes encoders that allow to feedback the wheels rotation and can be used to estimate the odometry.

Abstract
A robots simulation system is a basis need for any robotics application. With it, developers teams of robots can test their algorithms and make initial calibrations without risk of damage to the real robots, assuring safety. However, build these simulation environments is usually a time-consuming work, and when considering robot fleets, the simulation reveals to be computing expensive. With it, developers building teams of robots can test their algorithms and make initial calibrations without risk of damage to the real robots, assuring safety. An omnidirectional robot from the 5DPO robotics soccer team served to test this approach. The modeling issue was divided into two steps: modeling the motor's non-linear features and modeling the general behavior of the robot. A proper fitting of the robot was reached, considering the velocity robot's response.

Abstract
The following paper presents an improved, low cost, non-rigid joint that can be used in both robotic manipulators and leg-based traction robotic systems. This joint is an improvement over the previous one presented by the same authors because it is more robust. The design iterations are presented and the final system has been modeled including some nonlinear blocks. A control architecture is proposed that allows compliant control to be used under adverse conditions or in uncontrolled environments. The presented joint is a cost-effective solution that can be used when normal rigid joints are not suitable.