Deep Reinforcement Learning-Based Enhancement of Robotic Arm Target-Reaching Performance DOI Creative Commons
Ldet Honelign,

Yohanes Abebe,

Abera Tullu

и другие.

Actuators, Год журнала: 2025, Номер 14(4), С. 165 - 165

Опубликована: Март 26, 2025

This work investigates the implementation of Deep Deterministic Policy Gradient (DDPG) algorithm to enhance target-reaching capability seven degree-of-freedom (7-DoF) Franka Pandarobotic arm. A simulated environment is established by employing OpenAI Gym, PyBullet, and Panda Gym. After 100,000 training time steps, DDPG attains a success rate 100% an average reward −1.8. The actor loss critic values are 0.0846 0.00486, respectively, indicating improved decision-making accurate value function estimations. simulation results demonstrate efficiency in improving robotic arm performance, highlighting its potential for application improve manipulation.

Язык: Английский

DFDFTr + RAC-DAC: Dense Fusion with Deep Fusion Transformer and Realistic Actor-Critic combined with Decoupled Actor-Critic for end-to-end continuous multi-task robotic arm control DOI
Dang Thi Phuc,

Nguyen Truong Chinh,

Dau Sy Hieu

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126923 - 126923

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Deep Reinforcement Learning-Based Enhancement of Robotic Arm Target-Reaching Performance DOI Creative Commons
Ldet Honelign,

Yohanes Abebe,

Abera Tullu

и другие.

Actuators, Год журнала: 2025, Номер 14(4), С. 165 - 165

Опубликована: Март 26, 2025

This work investigates the implementation of Deep Deterministic Policy Gradient (DDPG) algorithm to enhance target-reaching capability seven degree-of-freedom (7-DoF) Franka Pandarobotic arm. A simulated environment is established by employing OpenAI Gym, PyBullet, and Panda Gym. After 100,000 training time steps, DDPG attains a success rate 100% an average reward −1.8. The actor loss critic values are 0.0846 0.00486, respectively, indicating improved decision-making accurate value function estimations. simulation results demonstrate efficiency in improving robotic arm performance, highlighting its potential for application improve manipulation.

Язык: Английский

Процитировано

0