Percorrer por autor "Pinto, Milena F."
A mostrar 1 - 10 de 21
Resultados por página
Opções de ordenação
- A Comparison of PID Controller Architectures Applied in Autonomous UAV Follow up of UGVPublication . Bonzatto Junior, Luciano; Berger, Guido S.; Braun, João A.; Pinto, Milena F.; Santos, Murillo Ferreira dos; Oliveira Júnior, Alexandre de; Nowakowski, Marek; Costa, Paulo; Wehrmeister, Marco A.; Lima, JoséThe cooperation between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has brought new perspectives and e!ectiveness to production and monitoring processes. In this sense, tracking moving targets in heterogeneous systems involves coordination, formation, and positioning systems between UGVs and UAVs. This article presents a Proportional-Integral-Derivative (PID) control strategy for tracking moving target operations, considering an operating environment between a multirotor UAV and an indoor UGV. Di!erent PID architectures are developed and compared to each other in the Gazebo simulator, whose objective is to analyze the control performance of the UAV when used to track the ground robot based on the identification of the ArUco fiducial marker. Computer vision techniques based on the Robot Operating System (ROS) are integrated into the UAV’s tracking system to provide a visual reference for the aircraft’s navigation system. The results of this study indicate that the PD, Cascade, and Parallel controllers showed similar performance in both trajectories tested, with the Parallel controller showing a slight advantage in terms of mean error and standard deviation, suggesting its suitability for applications that prioritize precision and stability.
- A Practical Approach to Teaching Differential Robot Control Using a Goal-to-Goal InterfacePublication . Amorim, Johann S.J. C. C.; Moraes, Camile A.; Neto, Accacio F. dos; Amorim, Josef G. J. C. C.; Santos, Patricia S.; Haddad, Diego; Pinto, Milena F.; Lima, JoséThis paper presents an interface to assist students in performing robot controllers. This application is designed to stabilize the movement of a goal-to-goal robot. The primary objective is to enhance the learning experience by offering an easy application that showcases the robot’s behavior based on its kinematic model. The paper outlines the various stages involved in developing and testing this simple interface, including a study of the kinematics of differential robots. It discusses the discrete- time equations for goal-to-goal behavior, the data required to obtain the controller, the application of the controller in a discrete microcontroller, and the development of code to simulate the robot’s behavior. The results show the developed interface and the possible outcomes through the use of this application in control classes.
- Adaptive path planning for fusing rapidly exploring random trees and deep reinforcement learning in an agriculture dynamic environment UAVsPublication . Castro, Gabriel G.R.; Berger, Guido; Cantieri, Álvaro R.; Teixeira, Marco; Lima, José; Pereira, Ana I.; Pinto, Milena F.Unmanned aerial vehicles (UAV) are a suitable solution for monitoring growing cultures due to the possibility of covering a large area and the necessity of periodic monitoring. In inspection and monitoring tasks, the UAV must find an optimal or near-optimal collision-free route given initial and target positions. In this sense, path-planning strategies are crucial, especially online path planning that can represent the robot’s operational environment or for control purposes. Therefore, this paper proposes an online adaptive path-planning solution based on the fusion of rapidly exploring random trees (RRT) and deep reinforcement learning (DRL) algorithms applied to the generation and control of the UAV autonomous trajectory during an olive-growing fly traps inspection task. The main objective of this proposal is to provide a reliable route for the UAV to reach the inspection points in the tree space to capture an image of the trap autonomously, avoiding possible obstacles present in the environment. The proposed framework was tested in a simulated environment using Gazebo and ROS. The results showed that the proposed solution accomplished the trial for environments up to 300 m3 and with 10 dynamic objects.
- Autonomous path follow UAV to assist onshore pipe inspection tasksPublication . Sousa, Lucas C.; Silva, Yago M.R. da; Castro, Gabriel G.R.; Souza, Caio L.; Berger, Guido; Lima, José; Brandão, Diego; Dias, João T.; Pinto, Milena F.Unmanned Aerial Vehicles (UAVs) are being deployed in different applications due to their reduced time execution to perform tasks, more extensive coverage area, and more risk minimization to humans. In the Oil & Gas industry, its use for inspection activities is even more attractive due to the large structures in these facilities. Therefore, this research proposes deploying an autonomous UAV system to inspect unburied pipelines of onshore O&G facilities. The proposed UAV guiding system is based on image processing techniques Canny edge detection and Hough Transform to detect the line and on a path follower algorithm to generate the trajectory. The proposed strategy was developed in Robot Operating System (ROS) and tested in a simulated environment considering the practical oper-ational. The same controller was tested on a physical UAV to validate the results obtained in previous simulations. The results demonstrated the effectiveness and feasibility of deploying the proposed strategy for this specific task and the cost reduction potential for real-life operations, as well as reduced potential risks to the physical integrity of the workers.
- A Comparison of Fiducial Markers Pose Estimation for UAVs Indoor Precision LandingPublication . Junior, Luciano Bonzatto; Berger, Guido; Oliveira Júnior, Alexandre de; Braun, João; Wehrmeister, Marco A.; Pinto, Milena F.; Lima, JoséCooperative robotics is exponentially gaining strength in scientific research, especially regarding the cooperation between ground mobile robots and Unmanned Aerial Vehicles (UAVs), where the remaining challenges are equipollent to its potential uses in different fields, such as agriculture and electrical tower inspections. Due to the complexity involved in the process, precision landing by UAVs onmoving robotic platforms for tasks such as battery hot-swapping is a major open research question. This work explores the feasibility and accuracy of different fiducial markers to aid in the precision landing process by a UAV on a mobile robotic platform. For this purpose, a TelloUAVwas used to acquire images at different positions, angles, and distances from ArUco, ARTag, and ArUco Board markers to evaluate their detection precision. The analyses demonstrate the highest reliability in the measurements performed through the ArUco marker. Future work will be devoted to using the ArUco marker to perform precision landing on a mobile robotic platform, considering the necessary adjustments to lessen the impact of errors intrinsic to detecting the fiducial marker during the landing procedure.
- Computer vision based path following for autonomous unammed aerial systems in unburied pipeline onshore inspectionPublication . Silva, Yago M.R. da; Andrade, Fabio A.A.; Sousa, Lucas C.; Castro, Gabriel G.R.; Dias, João T.; Berger, Guido; Lima, José; Pinto, Milena F.Unmanned Aerial Systems (UAS) are becoming more attractive in diverse applications due to their efficiency in performing tasks with a reduced time execution, covering a larger area, and lowering human risks at harmful tasks. In the context of Oil & Gas (O&G), the scenario is even more attractive for the application of UAS for inspection activities due to the large extension of these facilities and the operational risks involved in the processes. Many authors proposed solutions to detect gas leaks regarding the onshore unburied pipeline structures. However, only a few addressed the navigation and tracking problem for the autonomous navigation of UAS over these structures. Most proposed solutions rely on traditional computer vision strategies for tracking. As a drawback, depending on lighting conditions, the obtained path line may be inaccurate, making a strategy to force the UAS to continue on the path necessary. Therefore, this research describes the potential of an autonomous UAS based on image processing technique and Convolutional Neural Network (CNN) strategy to navigate appropriately in complex unburied pipeline networks contributing to the monitoring procedure of the Oil & Gas Industry structures. A CNN is used to detect the pipe, while image processing techniques such as Canny edge detection and Hough Transform are used to detect the pipe line reference, which is used by a line following algorithm to guide the UAS along the pipe. The framework is assessed by a PX4 flight controller Software-in-The-Loop (SITL) simulations performed with the Robot Operating System (ROS) along with the Gazebo platform to simulate the proposed operational environment and verify the approach’s functionality as a proof of concept. Real tests were also conducted. The results showed that the solution is robust and feasible to deploy in this proposed task, achieving 72% of mean average precision on detecting different types of pipes and 0.0111 m of mean squared error on the path following with a drone 2 m away from a tube.
- Control tunning approach and digital filter application for competitive line follower robotPublication . Amorim, Johann S.J.C.C.; Fernandes, Jefferson H.O.; Canella, André L.C.; Santos, Tatiana M.B.; Lima, José; Pinto, Milena F.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.
- Cooperative heterogeneous robots for autonomous insects trap monitoring system in a precision agriculture scenarioPublication . Berger, Guido; Teixeira, Marco; Cantieri, Álvaro R.; Lima, José; Pereira, Ana I.; Valente, António; Castro, Gabriel G.R.; Pinto, Milena F.The recent advances in precision agriculture are due to the emergence of modern robotics systems. For instance, unmanned aerial systems (UASs) give new possibilities that advance the solution of existing problems in this area in many different aspects. The reason is due to these platforms’ ability to perform activities at varying levels of complexity. Therefore, this research presents a multiple-cooperative robot solution for UAS and unmanned ground vehicle (UGV) systems for their joint inspection of olive grove inspect traps. This work evaluated the UAS and UGV vision-based navigation based on a yellow fly trap fixed in the trees to provide visual position data using the You Only Look Once (YOLO) algorithms. The experimental setup evaluated the fuzzy control algorithm applied to the UAS to make it reach the trap efficiently. Experimental tests were conducted in a realistic simulation environment using a robot operating system (ROS) and CoppeliaSim platforms to verify the methodology’s performance, and all tests considered specific real-world environmental conditions. A search and landing algorithm based on augmented reality tag (AR-Tag) visual processing was evaluated to allow for the return and landing of the UAS to the UGV base. The outcomes obtained in this work demonstrate the robustness and feasibility of the multiple-cooperative robot architecture for UGVs and UASs applied in the olive inspection scenario.
- Data fusion using ultra wideband time-of-flight positioning for mobile robot applicationsPublication . Lima, José; Pinto, André F.; Ribeiro, Francisco; Pinto, Milena F.; Pereira, Ana I.; Pinto, Vítor H.; Costa, Paulo Gomes daSelf-localization of a robot is one of the most important requirements in mobile robotics. There are several approaches to providing localization data. The Ultra Wide Band Time of Flight provides position information but lacks the angle. Odometry data can be combined by using a data fusion algorithm. This paper addresses the application of data fusion algorithms based on odometry and Ultra Wide Band Time of Flight positioning using a Kalman filter that allows performing the data fusion task which outputs the position and orientation of the robot. The proposed solution, validated in a real developed platform can be applied in service and industrial robots.
- Design and Development of an Omnidirectional Mecanum Platform for the RobotAtFactory 4.0 CompetitionPublication . Braun, João; Baidi, Kaïs; Bonzatto, Luciano; Berger, Guido; Pinto, Milena F.; Kalbermatter, Rebeca B.; Klein, Luan C.; Grilo, Vinicius F.S.B.; Pereira, Ana I.; Costa, Paulo Gomes da; Lima, JoséRobotics competitions are highly strategic tools to engage and motivate students, cultivating their curiosity and enthusiasm for technology and robotics. These competitions encompass various disciplines, such as programming, electronics, control systems, and prototyping, often beginning with developing a mobile platform. This paper focuses on designing and implementing an omnidirectional mecanum platform, encompassing aspects of mechatronics, mechanics, electronics, kinematics models, and control. Additionally, a simulation model is introduced and compared with the physical robot, providing a means to validate the proposed platform.
- «
- 1 (current)
- 2
- 3
- »