Control tunning approach and digital filter application for competitive line follower robot

This research describes the development of a control strategy to optimize a competitive line follower robot for standard races. The innovative approach stems from the WolfBotz team at CEFET/RJ, presenting a thorough exploration of mathematical foundations, hardware design, control analysis, and how to implement this system in a microcontroller. This research complements a previous work that shows all the regulations used in Brazilian competitions and describes the controllers used in the system, such as angular and linear control. This research emphasizes all the changes between the two versions of Line Follower robots. The emphasis on mathematical foundations and integrating digital signal processing techniques like digital filters set the stage for robust sensor data interpretation. The tuning and optimization of dual controllers for track stability and linear velocity regulation represent a significant innovation, augmenting the robot’s overall performance.The authors would like to thank CEFET/RJ and the Brazilian research agencies CAPES, CNPq, and FAPERJ for supporting this work. Besides, the authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).info:eu-repo/semantics/publishedVersio

The impact of educational robots as learning tools in specific technical classes in undergraduate education

The use of mobile robots in the classroom has gained increasing attention in recent years due to their potential to enhance student engagement and facilitate personalized learning. This research presents the insertion of mobile robots as a hands-on learning experience in Control and Servomechanisms II and Signal Processing II classes. This work also addresses the challenges and limitations of using mobile robots in the classroom, including technical difficulties. The students were evaluated during the code implementation in the practical exercises. Besides, a form was provided to them in order to assess the impact of these robots as part of the pedagogical practice. From the students’ positive feedback, it was possible to conclude that the mobile robots were well-accepted. Besides, the robots enhanced Control Systems classes and improved students’ learning outcomes.The authors would like to thank CEFET/RJ, UFF, UFRJ, and the Brazilian research agencies CAPES, CNPq, and FAPERJ. Besides, the authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).info:eu-repo/semantics/publishedVersio

Heterogeneous Multi-Robot Collaboration for Coverage Path Planning in Partially Known Dynamic Environments

This research presents a cooperation strategy for a heterogeneous group of robots that comprises two Unmanned Aerial Vehicles (UAVs) and one Unmanned Ground Vehicles (UGVs) to perform tasks in dynamic scenarios. This paper defines specific roles for the UAVs and UGV within the framework to address challenges like partially known terrains and dynamic obstacles. The UAVs are focused on aerial inspections and mapping, while UGV conducts ground-level inspections. In addition, the UAVs can return and land at the UGV base, in case of a low battery level, to perform hot swapping so as not to interrupt the inspection process. This research mainly emphasizes developing a robust Coverage Path Planning (CPP) algorithm that dynamically adapts paths to avoid collisions and ensure efficient coverage. The Wavefront algorithm was selected for the two-dimensional offline CPP. All robots must follow a predefined path generated by the offline CPP. The study also integrates advanced technologies like Neural Networks (NN) and Deep Reinforcement Learning (DRL) for adaptive path planning for both robots to enable real-time responses to dynamic obstacles. Extensive simulations using a Robot Operating System (ROS) and Gazebo platforms were conducted to validate the approach considering specific real-world situations, that is, an electrical substation, in order to demonstrate its functionality in addressing challenges in dynamic environments and advancing the field of autonomous robots.The authors also would like to thank their home Institute, CEFET/RJ, the federal Brazilian research agencies CAPES (code 001) and CNPq, and the Rio de Janeiro research agency, FAPERJ, for supporting this work.info:eu-repo/semantics/publishedVersio

Diversity of Brazilian Fungi

Abstract Knowledge about the Brazilian fungal diversity was, until 2010, recorded in few taxonomy and ecology publications, as well as in a handful of species lists. With the publication of the Catálogo de Plantas e Fungos do Brasil and the continued availability of an online list, it has been possible to aggregate this dispersed knowledge. The version presented here adds 2,111 species names to the 3,608 listed in 2010. A total of 5,719 species of fungi distributed in 1,246 genera, 102 orders and 13 phyla represents a considerable increase over the last five years, when only 924 genera and 78 orders were registered. Basidiomycota (2,741 species in 22 orders) and Ascomycota (1,881 species in 41 orders) predominate over other groups. The Atlantic Rainforest has the largest number of records, with 3,017 species, followed by Amazon Rainforest (1,050), Caatinga (999), Cerrado (638) and Pampa and Pantanal with 84 and 35 species, respectively. The Northeast region has the greatest richness (2,617 species), followed by Southeast (2,252), South (1,995), North (1,301) and Central-West (488 species). Regarding the States of the Federation, São Paulo with 1,846 species, Pernambuco with 1,611 and Rio Grande do Sul with 1,377 species are the most diverse

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora