Multi-robot path planning based on a deep reinforcement learning DQN algorithm

Multi-robot path planning based on a deep reinforcement learning DQN algorithm

The unmanned warehouse dispatching system of the ‘goods to people’ model uses a structure mainly based on a handling robot, which saves considerable manpower and improves the efficiency of the warehouse picking operation. However, the optimal performance of the scheduling system algorithm has high r...

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Bibliographic Details
Main Authors: Yang Yang, Li Juntao, Peng Lingling
Format: Article
Language:English
Published: Wiley 2020-06-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
multi-robot systems
mobile robots
learning (artificial intelligence)
path planning
scheduling system algorithm
warehouse picking operation
handling robot
unmanned warehouse dispatching system
path-planning problems
classic deep reinforcement learning algorithm
improved dqn algorithm converges
algorithmic process
robot path-planning problem
multirobot path planning
volume-based technology
q-learning algorithm
deep q-network algorithm
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2020.0024

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https://digital-library.theiet.org/content/journals/10.1049/trit.2020.0024

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