Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
Adaptive Trajectories for Robotic Manipulators
Submission Author:
João Victor Zanoni , SC , Brazil
Co-Authors:
João Victor Zanoni, Fernanda de Oliveira Ferreira, Leonardo Mejia Rincon
Presenter: João Victor Zanoni
doi://10.26678/ABCM.COBEM2023.COB2023-0857
Abstract
In response to continuous advancements in engineering and the rise of Industry 4.0, robotics has become a central point of interest, drawing widespread attention on a global scale. In this context, the problem of generating trajectories emerges as a significant challenge in the industry. In general, handling objects may require precision and stability to avoid damage and ensure the quality of the final product. Among many other challenges, the reliability of robots must be extremely high to allow and guarantee good safety. In light of these considerations, this paper proposes a new methodology for the automatic generation of optimized trajectories in robotic manipulators, anticipating and avoiding collisions with objects and obstacles. Grounded in foundational theories of industrial robotics and trajectory planning, our methodology employs a real-time spatial analysis algorithm to dynamically identify points of interest and obstacles within the robot manipulator's operational workspace. This enables us to generate an optimized trajectory that obviates the need for object removal or complete cessation of manipulator movement. As the central aim of this research project, we have devised an algorithmic methodology specifically tailored for future implementation in a Cartesian pick-and-place manipulator system. The proposed methodology allows for the execution of intelligent trajectory planning that not only avoids collision scenarios but also optimizes the robot's energy efficiency during task execution. The findings of this study substantiate the feasibility of offline intelligent trajectory planning. Moreover, the proposed methodology exhibits extensibility, suggesting its potential applicability to a broader spectrum of complex scenarios and heterogeneous manipulator architectures.
Keywords
Adaptive Trajectories, Optimization, Robotics, Robotic Manipulation
