Towards Collision Avoidance for Commodity Hardware Quadcopters with Ultrasound Localization
2015 (English)In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS), 2015, 193-203 p.Conference paper (Refereed)
We present a quadcopter platform built with commodity hardware that is able to do localization in GNSS-denied areas and avoid collisions by using a novel easy-to-setup and inexpensive ultrasound-localization system. We address the challenge to accurately estimate the copter's position and not hit any obstacles, including other, moving, quadcopters. The quadcopters avoid collisions by placing contours that represent risk around static and dynamic objects and acting if the risk contours overlap with ones own comfort zone. Position and velocity information is communicated between the copters to make them aware of each other. The shape and size of the risk contours are continuously updated based on the relative speed and distance to the obstacles and the current estimated localization accuracy. Thus, the collision-avoidance system is autonomous and only interferes with human or machine control of the quadcopter if the situation is hazardous. In the development of this platform we used our own simulation system using fault-injection (sensor faults, communication faults) together with automatically-generated tests to identify problematic scenarios for which the localization and risk contour parameters had to be adjusted. In the end, we were able to run thousands of simulations without any collisions, giving us confidence that also many real quadcopters can manoeuvre collision free in space-constrained GNSS-denied areas. ©2015 IEEE.
Place, publisher, year, edition, pages
2015. 193-203 p.
Engineering and Technology
IdentifiersURN: urn:nbn:se:hh:diva-28169DOI: 10.1109/ICUAS.2015.7152291ISBN: 978-1-4799-6009-5ISBN: 978-1-4799-6009-15OAI: oai:DiVA.org:hh-28169DiVA: diva2:808245
The 2015 International Conference on Unmanned Aircraft Systems (ICUAS), Denver, Colorado, USA, June 9-12, 2015
FunderEU, FP7, Seventh Framework ProgrammeKnowledge Foundation
This research has been funded through the KARYON EU project (Grant agreement no: 288195), the PROWESS EU project (Grant agreement no: 317820) and through EISIGS (grants from the Knowledge Foundation).2015-04-272015-04-272015-07-28Bibliographically approved