Blucher Engineering Proceedings

Outubro 2023, vol.10, num.5 - IX Simpósio Internacional de Inovação e Tecnologia
Full article - Open Access Idioma principal | Segundo principal

CONTROL OF INDUSTRIAL MANIPULATORS THROUGH REINFORCEMENT LEARNING: A STUDY OF THE PANDA MANIPULATOR IN A SIMULATED ENVIRONMENT

CONTROL OF INDUSTRIAL MANIPULATORS THROUGH REINFORCEMENT LEARNING: A STUDY OF THE PANDA MANIPULATOR IN A SIMULATED ENVIRONMENT

FERREIRA, MARCELO ALBERGARIA PAULINO F.; FRANKLIN, TANIEL SILVA; PINHEIRO, OBERDAN ROCHA

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The wide variety of scenarios in industrial environments requires intelligent robotics capable of directly interacting with the environment for problem-solving. Through reinforcement learning, robots can quickly adapt to new situations and learn from direct interaction with the environment. This work proposes a simulation environment based on Robotics Toolbox for Python to solve a classic problem of the inverse kinematics of manipulators, ensuring that the robot reaches the desired position without colliding with the obstacles present in the scene. The potential of this reinforcement learning method is illustrated through simulation using the Franka-Emika Panda manipulator trained by the Deep Deterministic Policy Gradient algorithm.

The wide variety of scenarios in industrial environments requires intelligent robotics capable of directly interacting with the environment for problem-solving. Through reinforcement learning, robots can quickly adapt to new situations and learn from direct interaction with the environment. This work proposes a simulation environment based on Robotics Toolbox for Python to solve a classic problem of the inverse kinematics of manipulators, ensuring that the robot reaches the desired position without colliding with the obstacles present in the scene. The potential of this reinforcement learning method is illustrated through simulation using the Franka-Emika Panda manipulator trained by the Deep Deterministic Policy Gradient algorithm.

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DOI: 10.5151/siintec2023-306030

Referências bibliográficas
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Como citar:

FERREIRA, MARCELO ALBERGARIA PAULINO F.; FRANKLIN, TANIEL SILVA; PINHEIRO, OBERDAN ROCHA ; "CONTROL OF INDUSTRIAL MANIPULATORS THROUGH REINFORCEMENT LEARNING: A STUDY OF THE PANDA MANIPULATOR IN A SIMULATED ENVIRONMENT", p-318-325. In: . São Paulo: Blucher, 2023.
ISSN 23577592, DOI 10.5151/siintec2023-306030

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