Exploring the robustness of insect-inspired visual navigation for flying robots

Dewar, Alex, Graham, Paul, Nowotny, Thomas and Philippides, Andrew (2020) Exploring the robustness of insect-inspired visual navigation for flying robots. ALIFE 2020: The 2020 Conference on Artificial Life, Online, July 13 - 18, 2020. Published in: Bongard, Josh, Lovato, Juniper, Hebert-Dufrésne, Laurent, Dasari, Radhakrishna and Soros, Lisa, (eds.) Artificial Life Conference Proceedings. (32) 668-677. The MIT Press

[img] PDF - Accepted Version
Available under License Creative Commons Attribution.

Download (8MB)


Having previously developed and tested insect-inspired visual navigation algorithms for ground-based agents, we here investigate their robustness when applied to agents moving in three dimensions, to assess if they are applicable to both flying insects and robots, focusing on the impact and potential utility of changes in height. We first demonstrate that a robot implementing a route navigation algorithm can successfully navigate a route through an indoor environment at a variety of heights, even using images saved at different heights. We show that that in our environments, the efficacy of route navigation is increased with increasing height and also, for those environments, that there is better transfer of information when using images learnt at a high height to navigate when flying lower, than the other way around. This suggests that there is perhaps an adaptive value to the storing and use of views from increased height. To assess the limits to this result, we show that it is possible for a ground-based robot to recover the correct heading when using goal images stored from the perspective of a quadcopter. Through the robustness of this bio-inspired algorithm, we thus demonstrate the benefits of the ALife approach.

Item Type: Conference Proceedings
Schools and Departments: School of Engineering and Informatics > Informatics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 17 Feb 2021 09:04
Last Modified: 23 Feb 2022 12:18
URI: http://sro.sussex.ac.uk/id/eprint/97187

View download statistics for this item

📧 Request an update
Project NameSussex Project NumberFunderFunder Ref
Brains on Board: Neuromorphic Control of Flying RobotsG1980EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILEP/P006094/1