Abstract
Performing tasks in agriculture, such as fruit monitoring or harvesting, requires perceiving the objects' spatial position. RGB-D cameras are limited under open-field environments due to lightning interferences. So, in this study, we state to answer the research question: How can we use and control monocular sensors to perceive objects' position in the 3D task space? Towards this aim, we approached histogram filters (Bayesian discrete filters) to estimate the position of tomatoes in the tomato plant through the algorithm MonoVisual3DFilter. Two kernel filters were studied: the square kernel and the Gaussian kernel. The implemented algorithm was essayed in simulation, with and without Gaussian noise and random noise, and in a testbed at laboratory conditions. The algorithm reported a mean absolute error lower than 10 mm in simulation and 20 mm in the testbed at laboratory conditions with an assessing distance of about 0.5 m. So, the results are viable for real environments and should be improved at closer distances.

Abstract
In recent years, as a result of population growth and the strong demand for energy resources, there has been an increase in greenhouse gas emissions. Thus, it is necessary to find solutions to reduce these emissions. This will make the use of electric vehicles (EV) more attractive and reduce the high dependency on internal combustion vehicles. However, the integration of electric vehicles will pose some challenges. For example, it will be necessary to increase the number of fast electric vehicle charging stations (FEVCS) to make electric mobility more attractive. Due to the high power levels involved in these systems, there are voltage drops that affect the voltage profile of some nodes of the distribution networks. This paper presents a methodology based on a genetic algorithm (GA) that is used to find the optimal location of charging stations that cause the minimum impact on the grid voltage profile. Two case studies are considered to evaluate the behavior of the distribution grid with different numbers of EV charging stations connected. From the results obtained, it can be concluded that the GA provides an efficient way to find the best charging station locations, ensuring that the grid voltage profile is within the regulatory limits and that the value of losses is minimized.

Abstract
The cooperation between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has brought new perspectives and effectiveness 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. Different 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.

Abstract
The world economy depends on information systems. Business value resides in the data stored on Information Technology (IT) systems and on the processes run with those data. Malicious actors target these IT systems to extract value out of them using different cyberattacks. Denial of Service (DoS) attacks are a common and harmful method to render IT systems connected to the Internet and, consequently, business processes running on top of them, unavailable. Cybersecurity researchers in the industry and academia are in search of early warning and detection systems to detect and mitigate these DoS attacks. This article proposes a novel early detection strategy for DoS attacks based on the information provided by Horizontal Visibility Graphs (HVG) and Natural Visibility Graphs (VG) obtained out of the network flows monitored at the receiving end of the attack. From the primary results obtained, this strategy can detect a DoS attack under 70ms and 30 packets. These results point out that the application HVGs and VGs is a relevant and promising research direction to prevent or mitigate the impact of a DoS attack.

Abstract
Human oversight can benefit scenarios with complex tasks, such as pallet docking and loading and unloading containers, beyond the current capabilities of autonomous systems without any failures. Furthermore, teleoperation systems allow remote control of mobile ground robots, especially with the surge of 5G technology that promises reliable and low latency communication. Current works research on exploring the latest features from the 5G standard, including ultra-Reliable Low-Latency Communication (uRLLC) and network slicing. However, these features may not be available depending on the Internet Service Provider (ISP) and communication devices. Thus, this work proposes a network architecture for the teleoperation of ground mobile robots in industrial environments using commercially available devices over the 5G Non-Standalone (NSA) standard. Experimental results include an evaluation of the network and End-to-End (E2E) latency of the proposed system. The results show that the proposed architecture enables teleoperation, achieving an average E2E latency of 347.19 ms.

Abstract
This paper discusses the emerging field of robotics, particularly focusing on motion planning for robotic manipulators. It highlights the need for simplification and standardization in robot implementation processes. Among several tools available, the paper focuses on the MoveIt tool due to its compatibility, popularity, and community contributions. However, the paper acknowledges some resistance in developing new applications with MoveIt, especially for researchers and beginners. To address this, the paper introduces an efficient, modular action server for interacting with the MoveIt framework. This pipeline simplifies parameter reconfiguration and provides a general solution for the motion planning problem. It can calculate trajectories for robotic manipulators without environmental collisions using a single server request and supports operation in different modes. The server was tested on an Universal Robots UR10 manipulator, demonstrating its ability to quickly plan paths for two test operations: an object pick-and-place mission and a collision avoidance test. The results were positive, achieving the set goals with minimal user-server interaction. This work represents a significant step towards more efficient and user-friendly robotic manipulation.