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Deep reinforcement learning for robotics: A survey of real-world successes
Reinforcement learning (RL), particularly its combination with deep neural networks,
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …
A survey on deep reinforcement learning algorithms for robotic manipulation
Robotic manipulation challenges, such as gras** and object manipulation, have been
tackled successfully with the help of deep reinforcement learning systems. We give an …
tackled successfully with the help of deep reinforcement learning systems. We give an …
Trends and challenges in robot manipulation
BACKGROUND Humans have a fantastic ability to manipulate objects of various shapes,
sizes, and materials and can control the objects' position in confined spaces with the …
sizes, and materials and can control the objects' position in confined spaces with the …
Intelligent disassembly of electric-vehicle batteries: a forward-looking overview
Retired electric-vehicle lithium-ion battery (EV-LIB) packs pose severe environmental
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …
Rearrangement: A challenge for embodied ai
D Batra, AX Chang, S Chernova, AJ Davison… - ar**
Gras**, in both biological and engineered mechanisms, can be highly sensitive to the
gripper and object morphology, as well as perception and motion planning. Here, we …
gripper and object morphology, as well as perception and motion planning. Here, we …