Prehensile and Non-Prehensile Robotic Pick-and-Place of Objects in Clutter Using Deep Reinforcement Learning

Prehensile and Non-Prehensile Robotic Pick-and-Place of Objects in Clutter Using Deep Reinforcement Learning

In this study, we develop a framework for an intelligent and self-supervised industrial pick-and-place operation for cluttered environments. Our target is to have the agent learn to perform prehensile and non-prehensile robotic manipulations to improve the efficiency and throughput of the pick-and-p...

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Bibliographic Details
Main Authors: Muhammad Babar Imtiaz, Yuansong Qiao, Brian Lee
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
prehensile
non-prehensile
robotic manipulation
Markov decision process
deep reinforcement learning
deep Q-network
Online Access:https://www.mdpi.com/1424-8220/23/3/1513

Internet

https://www.mdpi.com/1424-8220/23/3/1513

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