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Browsing INESCC-DL - Vários by Sustainable Development Goals (SDG) "08:Trabalho Digno e Crescimento Económico"
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- 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.
- 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.