Abstract
Computational thinking-related issues have had a specific track on TEEM Conference since 2016. This is the sixth edition of this track within the 2021 TEEM Conference edition. This year the papers are centered on programming and robotics, but the artificial intelligence topics increase their presence in the track.

Abstract
This article presents a comparison between a common type III controller and one based on a brain emotional learning paradigm (BELBIC) parameterized using a particle swarm optimization algorithm (PSO). Both strategies were evaluated regarding the set-point accuracy, disturbances rejection ability and control effort of a DC-DC buck converter. The simulation results suggests that, when compared to the common controller, the BELBIC leads to an increase in both set-point tracking and disturbances rejection ability while reducing the dynamics of the control signal.

Abstract
In this paper it is presented an educational experiment, that consists of a mechatronic system applied to demonstrate concepts such as prototyping, control, haptic feedback and the use of different sensors and actuators. The described mechatronic system is based on the use of two identical manipulators, being physical devices commonly used in the industry. The physical components of the manipulators were 3D printed, being the original model of each manipulator the EEZYBotArm MK2. This, already existent prototype was modified, with the necessary changes, to fulfill the requisites of the proposed system, being included load cells to provide measurement of the applied forces, and the robot gripper was also modified, being applied an electromagnetic actuator.

Abstract
In mobile robotics, since no requirements have been defined regarding accuracy for Battery Management Systems (BMS), standard approaches such as Open Circuit Voltage (OCV) and Coulomb Counting (CC) are usually applied, mostly due to the fact that employing more complicated estimation algorithms requires higher computing power; thus, the most advanced BMS algorithms reported in the literature are developed and verified by laboratory experiments using PC-based software. The objective of this paper is to describe the design of an autonomous and versatile embedded system based on an 8-bit microcontroller, where a Dual Coulomb Counting Extended Kalman Filter (DCC-EKF) algorithm for State of Charge (SOC) estimation is implemented; the developed prototype meets most of the constraints for BMSs reported in the literature, with an energy efficiency of 94% and an error of SOC accuracy that varies between 2% and 8% based on low-cost components.

Abstract
The importance of energy storage continues to grow, whether in power generation, consumer electronics, aviation, or other systems. Therefore, energy management in batteries is becoming an increasingly crucial aspect of optimizing the overall system and must be done properly. Very few works have been found in the literature proposing the implementation of algorithms such as Extended Kalman Filter (EKF) to predict the State of Charge (SOC) in small systems such as mobile robots, where in some applications the computational power is severely lacking. To this end, this work proposes an implementation of the two algorithms mainly reported in the literature for SOC estimation, in an ATMEGA328P microcontroller-based BMS. This embedded system is designed taking into consideration the criteria already defined for such a system and adding the aspect of flexibility and ease of implementation with an average error of 5% and an energy efficiency of 94%. One of the implemented algorithms performs the prediction while the other will be responsible for the monitoring.

Abstract
This paper presents a systematic mapping literature review about the mobile robotics competitions that took place over the last few decades in order to obtain an overview of the main objectives, target public, challenges, technologies used and final application area to show how these competitions have been contributing to education. In the review we found 673 papers from 5 different databases and at the end of the process, 75 papers were classified to extract all the relevant information using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. More than 50 mobile robotics competitions were found and it was possible to analyze most of the competitions in detail in order to answer the research questions, finding the main goals, target public, challenges, technologies and application area, mainly in education.