首页|Department of Mechanical Engineering Researchers Publish New Study Findings on Robotics (DDPG-based reinforcement learning for controlling a spatial three-secti on continuum robot)
Department of Mechanical Engineering Researchers Publish New Study Findings on Robotics (DDPG-based reinforcement learning for controlling a spatial three-secti on continuum robot)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on robotics are presented i n a new report.According to news reporting originating from Constantine,Algeria,by NewsRx correspondents,research stated,"This paper proposes an approach t o controlling a spatial three-section continuum robot using reinforcement learni ng (RL)." Our news editors obtained a quote from the research from Department of Mechanica l Engineering:"Rather than relying on traditional methods that use bending and orientation angles,this study utilizes the curvature of each section to achieve the desired position.The training process involves identifying a 3D workspace for the robot and utilizing a deep neural network to optimize its control polici es.The results demonstrate that the robot's end effector can follow a given tra jectory with a maximum error of 1 [1/mm] b ased on the generated curvature for each section.The Deep Deterministic Policy Gradients (DDPG) algorithm is employed to optimize the robot's control policies.Additionally,the developed DDPG algorithm is compared to the Deep Q-Network (D QN) from a precision standpoint,particularly during the tracking of a circular trajectory."
Department of Mechanical EngineeringCo nstantineAlgeriaAfricaEmerging TechnologiesMachine LearningReinforceme nt LearningRobotRobotics
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