Multirobot Coverage Path Planning Based on Deep Q-Network in Unknown Environment
Aiming at the problems of security, high repetition rate, and many restrictions of multirobot coverage path planning (MCPP) in an unknown environment, Deep Q-Network (DQN) is selected as a part of the method in this paper after considering its powerful approximation ability to the optimal action val...
Saved in:
| Main Authors: | Wenhao Li, Tao Zhao, Songyi Dian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/6825902 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Density-Based Detection Rapid Exploration Random Tree for Multirobot Formation Cooperative Path Planning
by: Yuzhuo Shi, et al.
Published: (2025-03-01) -
Intelligent Robot in Unknown Environments: Walk Path Using Q-Learning and Deep Q-Learning
by: Mouna El Wafi, et al.
Published: (2025-03-01) -
Dynamic Path Planning of Unknown Environment Based on Deep Reinforcement Learning
by: Xiaoyun Lei, et al.
Published: (2018-01-01) -
Modeling of Task Planning for Multirobot System Using Reputation Mechanism
by: Zhiguo Shi, et al.
Published: (2014-01-01) -
Reactive Path Planning Approach for Docking Robots in Unknown Environment
by: Peng Cui, et al.
Published: (2017-01-01)