Abstract
This paper describes the implementation of a simulated bioinspired 3D model, which was moved through segmented gestures using fractional calculation segmentation methods. It was observed that for the increase in the detection of such gestures from this segmentation an improvement in the recognition and standardization of gesture images using the FODPSO method would be obtained. We used the AlexNet neural network for training and recognition of the processed gestures, which resulted in a simulated 3D model of a spider moved by gestures recognized through a webcam, which had an accuracy of approximately 98% recognition through the neural network.

Abstract
Relation Extraction (RE) is part of Information Extraction (IE) and aims to obtain instances of semantic relations in textual documents. The countless possibilities of relations, the myriad of subjects, the difficulty in identifying emotions and the amount of unstructured and heterogeneous data, have challenged the researchers to define innovative and even more accurate methodologies. This paper presents the evaluation results obtained with a set of RE systems on identifying semantic relations in criminal police reports. We have evaluated different applications with documents in English and Portuguese. The results obtained give us useful insights to continue the research work, and to design the relation extraction system applied to related domain. © 2019, Springer Nature Switzerland AG.

Abstract
This paper compares optimal path planning algorithms based on a Genetic Algorithm and a Particle Swarm Optimization algorithm applied to multiple bioinspired robots in a 2D environment simulation. The planning objectives are related to the harvesting of an apple plantation in which three swarm of butterflies were run, counting the fruits on the ground to optimize the harvest in a cooperative way. Robotic swarms must travel through points on the map to count the fruits. The time for each swarm was also counted for the comparison results. © Springer Nature Switzerland AG 2019.

Abstract
This paper presents one methodology for teaching engineering students, which relies on open platform requiring basic knowledge of robotics, like mechanics, control or energy management. Walking robots are well known for being able to walk over rough terrain and adapt to various environments. Hexapod robots are chosen because of their better stability and higher number of different gaits. However, having to hold the whole weight of the body and a large number of actuators makes all walking robots less energetically efficient than wheeled robots. This platform endows students with an intuitive learning for current technologies, development and testing of new algorithms in the area of mobile robotics and also in generating good team-building. © 2019, Springer Nature Switzerland AG.

Abstract
The paper describes the use of computer applications on education for industrial robotic systems. Robotics evolved as a central issue in teaching for scientific and engineering courses and inherently encompasses a spectrum of sciences and technologies and qualification levels. However, most current teaching approaches, related to robotics, concentrate on individual aspects or small student groups and do not involve dangerous situations. With a mixed-reality robotics teaching, a true interdisciplinary setup can be reached, this approach has been used in a robotics course at higher education, to prepare students for future activities in industry and also in research. This active learning experience approach in the field of Industrial Robotics was implemented in a Master degree on Electrical Engineering.

Abstract
This paper presents a Pattern Recognition System, which can be used in classification applications for hand gestures for control of robotic arms. The system based in three steps, uses feature matching for extracting objects from a scene, edge detector and deep learning. The use of extraction of the region of interest and edges segmentation reduces the amount of processing required to recognize signals, thus speeding up the recognition process. Experimental classification results were positive with good statistical results. The presented data were tested considering four different types of segmentation implementations.