5 Result(s)
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Article
A stable data-augmented reinforcement learning method with ensemble exploration and exploitation
Learning from visual observations is a significant yet challenging problem in Reinforcement Learning (RL). Two respective problems, representation learning and task learning, need to solve to infer an optimal ...
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Article
A Graph-Based Deep Reinforcement Learning Approach to Gras** Fully Occluded Objects
Gras** in cluttered scenes is an important issue in robotic manipulation. The cooperation of gras** and pushing actions based on reinforcement learning is an effective means to obtain the target object whe...
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Article
Offline reinforcement learning with anderson acceleration for robotic tasks
Offline reinforcement learning (RL) can learn effective policy from a fixed batch of data without interaction. However, the real-world requirements, such as better performance and high sample efficiency, put s...
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Article
SOAR Improved Artificial Neural Network for Multistep Decision-making Tasks
Recently, artificial neural networks (ANNs) have been applied to various robot-related research areas due to their powerful spatial feature abstraction and temporal information prediction abilities. Decision-m...
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Article
Fine semantic map** based on dense segmentation network
This paper proposes a fine semantic map** method using dense segmentation network (DS-Net) to obtain good performance of semantic map** fusion. First, the RGB image and the depth image are used to generate...
