Experimental validation of the selective velocity obstacle method for autonomous collision avoidance

Cherry Cheung, Yazdi I. Jenie, Erik Jan van Kampen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Unmanned aerial vehicle (UAV) applications are increasing and there is a need for safe operations in terms of avoidance. The Velocity Obstacle (VO) method uses position and velocity vectors to determine if a collision is going to happen; an adaptation of the VOmethod is called the Selective Velocity Obstacle (SVO) method and adds navigation modes and right of way rules for cooperative flights. The characteristics of the SVO-method have been evaluated before in a simulated environment, but the contribution of this paper is an experimental validation of the SVO-method by including the factors that are neglected in simulation such as noise, delay and unmodeled dynamics. Additionally, it is shown how adaptations need to be made when actual drones are used for avoidance. Multiple situations are tested where two UAVs are flown on trajectories to create colliding situations. For the experimental setup, the SVO-method is implemented on a Parrot® AR. Drone 2.0 while an OptiTrack system provides position and velocity data. The Paparazzi autopilot system uses this data for its flight plans to fly autonomously between waypoints. The results of the experiment show that the SVO-method is a safe cooperative avoidance method.

Original languageEnglish
Title of host publicationAIAA Guidance, Navigation, and Control Conference, 2017
PublisherAmerican Institute of Aeronautics and Astronautics Inc. (AIAA)
Number of pages18
ISBN (Electronic)9781624104503
DOIs
Publication statusPublished - 2017
EventAIAA Guidance, Navigation, and Control Conference, 2017 - Grapevine, United States
Duration: 9 Jan 201713 Jan 2017
https://doi.org/10.2514/MGNC17

Conference

ConferenceAIAA Guidance, Navigation, and Control Conference, 2017
CountryUnited States
CityGrapevine
Period9/01/1713/01/17
Internet address

Fingerprint Dive into the research topics of 'Experimental validation of the selective velocity obstacle method for autonomous collision avoidance'. Together they form a unique fingerprint.

  • Cite this

    Cheung, C., Jenie, Y. I., & van Kampen, E. J. (2017). Experimental validation of the selective velocity obstacle method for autonomous collision avoidance. In AIAA Guidance, Navigation, and Control Conference, 2017 [AIAA 2017-1912] American Institute of Aeronautics and Astronautics Inc. (AIAA). https://doi.org/10.2514/6.2017-1912