Real-time hierarchical map segmentation for coordinating multi-robot exploration
Coordinating a team of autonomous agents to explore an environment can be done by partitioning the map of the environment into segments and allocating the segments as targets for the individual agents to visit. However, given an unknown environment, map segmentation must be conducted in a continuous...
Saved in:
Main Authors: | Luo, Tianze, Chen, Zichen, Subagdja, Budhitama, Tan, Ah-Hwee |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/164995 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Real-time hierarchical map segmentation for coordinating multi-robot exploration
by: LUO, Tianze, et al.
Published: (2023) -
End-to-end deep reinforcement learning for multi-agent collaborative exploration
by: CHEN, Zichen, et al.
Published: (2019) -
End-to-end deep reinforcement learning for multi-agent collaborative exploration
by: Chen, Zichen, et al.
Published: (2021) -
Multi-agent collaborative exploration through graph-based deep reinforcement learning
by: LUO, Tianze, et al.
Published: (2019) -
A coordination framework for multi-agent persuasion and adviser systems
by: Subagdja, Budhitama, et al.
Published: (2020)