Abstract
This paper describes the several steps to build an elaborate flight simulator cockpit, where the hardware is designed based on Mechatronic principles and the proposed software was developed using agile methodologies to create a Cyber-Physical System (CPS). Furthermore, this research attempts to simulate the real environment from an aircraft as close as possible with a real scale developed cockpit. Based on this, the presented paper contributions include: (1) The implementation of a complex dynamic system such as a CPS, where the Mechatronic system is part of it; (2) The deployment of a scale model of an Airbus A32x aircraft (one of the most used), integrating into a mathematical model adapted to the operation of an aircraft flight simulation system, regarding the physical forces involved. This project is also used to captivate the students' motivation to the areas of technology such as electronics and programming and permits its development as a student project and thesis. Results allow validating the proposed cockpit.

Abstract
Rescuing survivors in unknown environment can be extreme difficulty. The use of UAVs to map the environment and also to obtain remote information can benefit the rescue tasks. This paper proposes an organizational system for multi-UAVs to map indoor environments that have been affected by a natural disaster. The robot’s organization is focused on avoiding possible collisions between swarm’s members, and also to prevent searching in locations that have already discovered. This organizational approach is inspired by bees behavior. Thus, the multi- UAVs must search, in a collaborative way, in order to map the scenario in the shortest possible time and, consequently, to travel the shortest reasonable distance. Therefore, three strategies were evaluated in a simulation scenario created in the V-REP software. The results indicate the feasibility of the proposed approach and compare the three plans based on the number of locations discovered and the path taken by each UAV. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
This paper discusses a novel collective sensing approach using autonomous sensors specially designed to monitor gas leaks and search for gas sources. The proposed collective behavior aims to improve the gas-source search by sharing information between mobile sensors and reducing the risks associated with gas leakage. The group acts as a composite sensor that can move independently to search for an optimal sensing zone. The autonomous searching behavior is bio-inspired by colonies of bacteria that continuously seek energy sources throughout their existence. Each sensor makes its own autonomous search decision, considering the group sense, to move in the direction of a better energy source. The collective approach is based on autonomous agents sharing information to achieve a collective sense of gas perception and utilizes more intelligent searching. The method is evaluated in a cyber-physical system specially developed to safely experiment with gases and mobile sensors while reproducing the realistic dynamic behavior of the gas. Experiments are performed to clarify the collective gas-sensing contributions, and the gas search is compared through multiple mobile sensors with and without collective sensing. The proposed approach is evaluated in an unhealthy environment to elucidate its effectiveness. In addition to presenting the related differences between collective and individual sensory approaches, this work contributes with analyzes of the scalability of mobile gas sensing systems. This work also contributed as a simulated semi-physical experimental system to test algorithms' performance before applying it to practice.

Abstract
Industrial Manipulators were becoming used more and more at industries since the third industrial revolution. Actually, with the fourth one, the paradigm is changing and the collaborative robots are being accepted for the community. It means that smaller manipulators with more functionalities have been used and installed. New approaches have appeared to teach students according to the new robot’s capabilities. The DOBOT robot is an example of that since it captivates the student’s attention with an uncomplicated programming front-end, tools, grippers and extremely useful for teaching STEM. This paper proposes a dynamic based simulation environment that can be used to teach, test and validate solutions to the DOBOT robot. By this way, the student can try and validate, at their homework without the real robot, the developed solutions and further test them at the laboratory with the real robot. Currently, remote testing and validation without the use of a real robot is an advantage. The comparison of the provided simulation environment and the real robot is presented in the approach. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
The advancement of technology and techniques applied to robotics contributes to increasing the quality of life and safety of humanity. One of the most widespread applications of mobile robotics is related to monitoring indoor environments. However, due to factors such as the size of the environment impacting the monitoring response, battery autonomy, and autonomous navigation in environments with unknown obstacles, they are still significant challenges in the diffusion of mobile robotics in these areas. Strategy adopting multiple robots can overcome these challenges. This work presents an approach to use multi-robots in hazardous environments with gas leakage to perform spatial mapping of the gas concentration. Obstacles arranged in the environment are unknown to robots, then a fuzzy control approach is used to avoid the collision. As a result of this paper, spatial mapping of an indoor environment was carried out with multi-robots that reactively react to unknown obstacles considering a point gas leak with Gaussian dispersion.

Abstract
Data acquisition by electromyography, as well as the muscle stimulation, has become more accessible with the new developments in the wearable technology and medicine. In fact, for treatments, games or sports, it is possible to find examples of the use of muscle signals to analyse specific aspects related, e.g., to disease, injuries or movement impulses. However, these systems are usually expensive, does not integrate data acquisition with the muscle stimulation and does not exhibit an adaptive control behaviour that consider the pathology and the patient response. This paper presents a wearable system that integrates the signal acquisition and the electrostimulation using dry thin-film titanium-based electrodes. The acquired data is transmitted to a mobile application running on a smartphone by using Bluetooth Low Energy (BLE) technology, where it is analysed by employing artificial intelligence algorithms to provide customised treatments for each patient profile and type of pathology, and taking into consideration the feedback of the acquired electromyography signal. The acquired patient's data is also stored in a secure cloud database to support the physician to analyse and follow-up the clinical results from the rehabilitation process.