University of East Anglia Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
University College London Featured PhD Programmes

Distributed, dynamic path planning and control of Unmanned Aerial Vehicle Swarms for 3D mapping and geospatial data collection

Project Description

The ubiquity of Geospatial Information Systems (GIS) is fuelling a growing need to collect spatial data quickly, efficiently and regularly. This project will develop novel methods to aid the creation of rich and timely data and in so doing will empower people to make information-based decisions.

Many geospatial data collection tasks require many images taken from various perspectives. Unmanned Aerial Vehicles (drones) can be used for this task, but with a single drone it can take several hours before data collection is completed. Furthermore, with a pre-determined flight path, and data post-processing (e.g. synthetic aperture methods based upon a “lawn-mower” flight trajectory), it is often only known after the campaign whether the collected data is of sufficient quality for the geospatial application at hand, and the data may suffer ‘gaps’, e.g. from feature occlusion. Instead, we’d like to investigate the use of a drone swarm to speed up capture. By enabling the drones to co-ordinate in real-time, we believe that completion times can be significantly shortened. This requires new distributed and scalable drone co-ordination and flight-planning algorithms. Research will include new real-time collaborative and distributed algorithms for allocating data collection tasks to drones, maintaining the correct spatial relationship between each drone, and for time-efficient path planning based on data observed and current drone positions. Network connectivity is required to ensure that drones make consistent decisions and to guarantee that the entire swarm can be controlled by a single operator instead of having one operator per drone. Such communication requirements need to be included into the dynamic path planning algorithm.

The innovations in drone co-ordination and dynamic path planning can be applied to important geospatial sensing and data-collection tasks, including computer vision, RADAR and LIDAR surveying and tracking of targets through complex terrains.

Funding Notes

The Geospatial Research Institute Toi Hangarau (GRI) is pleased to offer ONE PhD scholarship as a supplement to the University of Canterbury PhD scholarship. This scholarship is available only to a new PhD applicant who will complete research towards an approved geospatial project. The scholarship value is NZ$9,000 per year plus up to NZ$2,000 for travel and other costs per year, in addition to the University of Canterbury scholarship: the total package is worth up to NZ$33,000 per year, plus tuition fees. For more details and to apply, please see here: View Website

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully

FindAPhD. Copyright 2005-2020
All rights reserved.