Hybridized trajectory generation and many-objectives optimization for multi-agent quadrotor UAVs

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Hybridized trajectory generation and many-objectives optimization for multi-agent quadrotor UAVs

This research generates a large collection of optimized trajectories for multi-agent quadrotors. The hybridized algorithm extracts trajectories with various trade-off for all agents without discrimination. This allows the resources of all agents to contribute towards the completion of a task. Tw...

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Bibliographic Details
Main Author:	Tharumanathan, Premeela
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2018
Online Access:	https://eprints.nottingham.ac.uk/48060/

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