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- Robotic Path Planning Algorithms for Additive Manufacturing Using Advanced Simulation ToolsPublication . Ferreira, Marco; Costelha, Hugo; Conde Bento, Luis; Neves, CarlosRobotics-based additive manufacturing (AM), or 3D printing, enables flexible printing systems. This paper analyses path planning algorithms for robotic manipulators aiming at dynamic AM environments. Using the cuRobo library, the study evaluates the path planning algorithm MotionGen and Model Predictive Control (MPC) using NVIDIA’s Isaac Sim with ROS2 and MoveIt2. Docker provided a modular development environment, and an Intel RealSense camera was used to enable real-world and real-time obstacle detection. Results show that MotionGen outperforms MPC in energy consumption and time efficiency, generating smoother and more efficient trajectories, more suitable for real-time AM contexts. The project shows the potential of advanced robotic control algorithms to optimize AM, using NVIDIA’s Isaac platform. Future work will focus on applying this to real robots.
- Industrial Robot Trajectory Generation and Execution for 3D Printing using an ABB IRB 1200Publication . Cavalcanti, Marcella; Costelha, Hugo; Neves, CarlosThe use of industrial robots in additive manufacturing processes has become increasingly important, offering more flexibility and the capability of multi-directional printing. This integration facilitates the production of more complex geometries, free from the limitations of small build volumes and support structures, opening new possibilities for innovation in advanced manufacturing systems. As the complexity of the printed structures grows, optimizing robot trajectories is essential to ensure high-quality results. This work presents a comparative analysis of robot trajectory generation and execution using ABB's 3D Printing Power Pack and generated RAPID coding in both simulated and real environments. The objective is to assess the use of the Power Pack in term of trajectory accuracy and efficiency, as well as how the simulated results compare with the real ones, considering the use-case of 3D printing. To support this analysis, a "test pattern" was designed to account for different trajectories, consisting of a single line extrusion path featuring long linear segments, corners, and curved sections. The path was converted into both G-code and RAPID code. The G-code was first validated on a standard 3D printer and then used as input in the 3D Printing Power Pack application to generate a RAPID program for the robot. Separately, another RAPID program was created manually to execute the same path, based on the G-code. Both programs were executed on a simulated environment in RobotStudio, and on an ABB IRB 1200 robot. Throughout the tests, the robot’s Tool Center Point (TCP) position was captured using ABB’s Externally Guided Motion (EGM) application.
- Agile Accessibility Assessment: Development and Evaluation of Native SoftwarePublication . de Sousa e Silva, João; Pereira, António; Ferreira, Rui Bragança; Gonçalves, RamiroThe information and communication technologies (ICT) have the potential to improve the quality of life of individual with functional particularities, potentiating their activity in society, as well supplying the conditions for a prolonged active life, counter acting the natural age related lost of faculties. As such, the software component – of ICT – is lacking a good and attentive construction to these functioning details which, often, are of difficult assessment. Adding to these constrains, the existing information is, not exclusively but especially, focused on Web contents. Attending to these matters, a checklist of proposals has been elaborated, and presented in this paper, that tries to cover these flaws, allowing for an evaluation of the accessibility of Integrated Development Environments (IDE), their capacity of generating accessible software – native software and not Web contents -, and even the accessibility of the final product – the native software. Conceived through the reutilization and inspired on the general knowledge created by the Web Accessibility Initiative (WAI), the drafts of this checklist are easily understandable and applicable. With the objective of facilitating the work of information systems technician who may already have concerns regarding these topics, it further has the important potential of encouraging agents to initiate themselves into the cares that this are requires.
- Network reconfiguration to improve reliability and efficiency in distribution systemsPublication . Vitorino, Romeu; Pires Neves, Luís; Jorge, H. M.This paper presents a new method to improve reliability and also minimize active power losses in radial distribution systems (RDS) through a process of network reconfiguration. The methodology adopted to enhance reliability, uses the Monte Carlo (MC) simulation and an historical data of the network such as the severity of the potential contingencies in each branch. Due to the greater number of possible configurations and the need of an efficient search, is also used an improved genetic algorithm (IGA), with adaptive crossover and mutation probabilities and with other new features. The method analyses the RDS in a perspective of optimization considering no investment, and a perspective of optimization where is given the possibility to place a limited number of tie-switches, defined by a decision agent, in certain branches. The effectiveness of the proposed method is demonstrated through the analysis of a 69 bus RDS.
- Load forecasting based on neural networks and load profilingPublication . Sousa, João; Pires Neves, Luís; H. M. JorgeThis work presents a novel perspective of load forecasting based on neural networks and load profiling. In addition to the variables that are typically used to predict future load demand, such as past load values, meteorological variables, seasonal effects or macroeconomic indexes, it is expected that the use of load profiles and detailed information of individual consumers could favor the forecasting process. The methodology can be extended to different temporal horizons being predicted and the eventual threat of overparametrization is attenuated by the use of neural networks since the complexity of the model does not necessarily depends on the number of its weights and biases, as some of these parameters might be found irrelevant in the process. Another way to reduce the risk of overparametrization and overfitting is through the use of a considerable number of data points (whenever historical data is available) to train the network.
- Impact of load and generation price uncertainties in spot pricesPublication . Gomes, Bruno A.; Saraiva, João T.; Pires Neves, LuísIn this paper it is presented a formulation for the DC Optimal Power Flow problem considering load and generation cost uncertainties and the corresponding solution algorithms. The paper also details the algorithms implemented to allow the integration of losses on the results as well the algorithm developed to compute the nodal marginal price in the presence of such uncertainties. Since loads and generation costs are represented by fuzzy numbers, nodal marginal prices are no longer represented by deterministic values, but instead, by membership functions. To illustrate the application of the proposed algorithms, this paper also includes results based on a small 3 bus system and on the IEEE 24 bus/38 branch test system.
- Network reconfiguration using a genetic approach for loss and reliability optimization in distribution systemsPublication . Vitorino, Romeu; Jorge, Humberto M. M.; Pires Neves, LuísThis paper presents a new method to improve reliability and also minimize losses in radial distribution systems (RDS), trough a process of network reconfiguration, using a genetic algorithm approach. The methodology adopted to enhance reliability, uses the Monte Carlo simulation and an historical data of the network such as the level of reliability and the severity of potential contingencies in each branch. The method analyses the RDS in two perspectives. A first perspective of optimization considering no investment, therefore using only the switches presented in the network, and a second perspective of optimization where is given the possibility to place a limited number of tie-switches and thus get better results. Here, the number of tie-switches and the branches that can receive them are defined by a decision agent. The effectiveness of the proposed method is demonstrated through the analysis of a 69 bus RDS.
- Short-term load forecasting using information obtained from low voltage load profilesPublication . Sousa, João; Pires Neves, Luís; Humberto M.M. JorgeRecent researches in load forecasting are quite often based on the use of neural networks in order to predict a specific variable (maximum demand, active electric power or hourly consumption) using past values of the same variable and other exogenous factors proved to influence the value being predicted. This work aims to explore different input patterns in neural networks incorporating information derived from load profiles of different consumers' classes.