Collision avoidance for automated guided vehicles using deep reinforcement learning

It is crucial yet challenging to develop an efficient collision avoidance policy for robots. While centralized collision avoidance methods for multi-robot systems exist and they are often more accurate and error-free, decentralized methods have the potential to reduce the prohibitive computation whe...

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Bibliographic Details
Main Author: Qin, Yifan
Other Authors: Xie Lihua
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/139736
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Institution: Nanyang Technological University
Language: English
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