Dynamic obstacle avoidance and evaluation base on neural network

Dynamic obstacle avoidance and evaluation base on neural network

The aim of this dissertation is to address the issue of dynamic obstacle avoidance in robotics. By combining genetic algorithms and neural network technology, a novel dynamic obstacle avoidance control system is developed. The dissertation introduces the Neuro Evolution of Augmenting Topologies (NEA...

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Bibliographic Details
Main Author: Li, Qi
Other Authors: Ling Keck Voon
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2023
Subjects:
Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Online Access:https://hdl.handle.net/10356/171546

Internet

https://hdl.handle.net/10356/171546

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