ArticleFrontiers in neuroinformatics2023
An enhanced deep deterministic policy gradient algorithm for intelligent control of robotic arms.
Article in Frontiers in neuroinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Deep Reinforcement Learning of Mobile Robot Navigation in Dynamic Environment: A Review.Sensors (Basel, Switzerland) · 2025Review
- Adaptive emergency response and dynamic crowd navigation for mobile robot using deep reinforcement learning.Frontiers in robotics and AI · 2025Article
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5 authors.
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Abstract
Aiming at the poor robustness and adaptability of traditional control methods for different situations, the deep deterministic policy gradient (DDPG) algorithm is improved by designing a hybrid function that includes different rewards superimposed on each other. In addition, the experience replay mechanism of DDPG is also improved by combining priority sampling and uniform sampling to accelerate the DDPG's convergence. Finally, it is verified in the simulation environment that the improved DDPG algorithm can achieve accurate control of the robot arm motion. The experimental results show that the improved DDPG algorithm can converge in a shorter time, and the average success rate in the robotic arm end-reaching task is as high as 91.27%. Compared with the original DDPG algorithm, it has more robust environmental adaptability.
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