Bio-inspired path planning for unmanned air vehicles in urban environments

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)


Small Unmanned Air Vehicles (SUAVs) are quick launching and fly at low altitudes offering a range of uses within urban environments. Complex urban wind flows present control issues for small platforms and current battery technology does not provide the required endurance for such missions. However, birds of a comparable size are able to manage these flows and reduce energy costs by exploiting the wind environment. This thesis initially explores the flight paths of urban gulls measured with an ornithodolite while performing orographic soaring along a row of buildings. The air flow was generated using Computational Fluid Dynamics (CFD) and it was found that gulls modulated their flight paths with changing wind conditions and only used part of the potential flow field which could offer the advantage of robust control in gusts. Further flight strategies were studied by fitting 11 urban gulls with Global Positioning System (GPS) backpacks. The gulls were found to significantly reduce the energetic cost of commuting flights by exploiting a combination of thermal and orographic updraughts generated by urban environments. Gulls adjusted their flight speeds in response to headwinds and updraughts minimising their cost of transport and by closely matching their flapping and soaring velocities the gulls reduced energy costs by up to a third. Finally, the velocity optimisation strategy used by the gulls was implemented in a path planner. Global and local solution trajectories were found for the same wind conditions as 27 gull flights. The path planner was found to outperform the gulls implementing a higher percentage of soaring and selecting shorter routes. The simulated trajectories highlighted that static and dynamic soaring strategies could be used in complex flow conditions to save energy. Cost ratios for powered and soaring flight were varied to a typical SUAV platform, the result indicated that energy costs could be halved in range based missions for urban SUAVs.
Date of Award23 Jun 2020
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorShane P Windsor (Supervisor) & Arthur G Richards (Supervisor)


  • bio-inspired
  • UAV
  • bird flight
  • path planning
  • wind model
  • urban
  • bio-logging

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