Goal-seeking navigation based on multi-agent reinforcement learning approach
Mobile robotics has been applied in many fields of industry and has been an impact on many industries. Most modern industries depend on mobile robots ranging from indoor to outdoor applications such as robot vacuum to robot delivery. The most important aspect of mobile robots is the navigation algor...
Saved in:
Main Author: | Abdul Jalil, Abdul Muizz |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/99333/1/AbdulMuizzAbdulMSKE2022.pdf http://eprints.utm.my/id/eprint/99333/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149973 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK
by: SINGH, NIHARIKA
Published: (2021) -
AUTONOMOUS VISUAL NAVIGATION AND COLLISION-FREE STRATEGY
USING DEEP REINFORCEMENT LEARNING
by: EJAZ, MUHAMMAD MUDASSIR
Published: (2021) -
Self-organized behaviour in a modified multi-agent simulation model based on physical force approach
by: Khamis, N., et al.
Published: (2016) -
AUGMENTED REALITY BASED INDOOR POSITIONING NAVIGATION TOOL.
by: Abdul Malek, Muhammad Fadzly
Published: (2016) -
Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
by: Nadheer Abdulridha, Shalash
Published: (2015)