Abstract
Localization in GPS-denied environments has become a bottleneck problem for small unmanned aerial vehicles (UAVs). Smartphones equipped with multi-sensors and multi-core processors provide a choice advantage for small UAVs for their high integration and light weight. However, the built-in phone sensor has low accuracy and the phone storage and computing resources are limited, which make the traditional localization methods unable to be readily converted to smartphone-based ones. The paper aims at exploring the feasibility of the phone sensors, and presenting a real-time, less memory autonomous localization method based on the phone sensors, so that the combination of “small UAV+smartphone” can operate in GPS-denied areas regardless of the overload problem. Indoor and outdoor flight experiments are carried out, respectively, based on an off-the-shelf smartphone and a XAircraft 650 quad-rotor platform. The results show that the precision performance of the phone sensors and real-time accurate localization in indoor environment is possible.
Highlights
In recent years, small unmanned aerial vehicles (UAVs) have shown great application potential in the field of rescue and relief work [1,2], environment exploration [3,4], and so on, for their light weight and agile movement
The common standard and testing methods have not been formulated in the research field on these micro-electro-mechanical system (MEMS) sensors [7], so the first question is supposed to determine which sensors in mobile phones can be used for UAV localization
The two papers mainly focus on the on-board hardware implementation and flight controlling, while the mapping and localization algorithm was chosen from the existing approaches, which integrates the visual odometry (VO)/visual simultaneous localization and mapping (VSLAM) algorithm and IMU sensor measurements based on a filter framework
Summary
Small unmanned aerial vehicles (UAVs) have shown great application potential in the field of rescue and relief work [1,2], environment exploration [3,4], and so on, for their light weight and agile movement. The high integration and improving performance of the mobile phone make it advantageous for the airborne equipment of the small UAV. It faces great challenges mainly from the following two points: 2. The common standard and testing methods have not been formulated in the research field on these MEMS sensors [7], so the first question is supposed to determine which sensors in mobile phones can be used for UAV localization. The operation of these algorithms requires sufficient storage space and computing resources to store environment maps, loop closure detection, and local/global optimization, which challenge the performance of the mobile phone
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
