Deep reinforcement learning for robotics: A survey of real-world successes

C Tang, B Abbatematteo, J Hu… - Annual Review of …, 2024 - annualreviews.org
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 …

A survey on deep reinforcement learning algorithms for robotic manipulation

D Han, B Mulyana, V Stankovic, S Cheng - Sensors, 2023 - mdpi.com
Robotic manipulation challenges, such as gras** and object manipulation, have been
tackled successfully with the help of deep reinforcement learning systems. We give an …

Trends and challenges in robot manipulation

A Billard, D Kragic - Science, 2019 - science.org
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 …

Intelligent disassembly of electric-vehicle batteries: a forward-looking overview

K Meng, G Xu, X Peng, K Youcef-Toumi, J Li - … , Conservation and Recycling, 2022 - Elsevier
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 …

Rearrangement: A challenge for embodied ai

D Batra, AX Chang, S Chernova, AJ Davison… - ar**
K Becker, C Teeple, N Charles, Y Jung, D Baum… - Proceedings of the …, 2022 - pnas.org
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 …