Vision-based obstacle avoidance for UAVs

Yoko Watanabe, Anthony J. Calise, Eric N. Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

83 Scopus citations


This paper describes a vision-based navigation and guidance design for UAVs for a combined mission of waypoint tracking and collision avoidance with unforeseen obstacles using a single 2-D passive vision sensor. An extended Kalman filter (EKF) is applied to estimate a relative position of obstacles from vision-based measurements. The stochastic 2-test value is used to solve a correspondence problem between the measurements and the estimates that have been already obtained by then. A collision cone approach is used as a collision criteria in order to examine if there is any obstacle that is critical to the vehicle. A guidance strategy for collision avoidance is designed based on a minimum-effort guidance (MEG) method for multiple target tracking. The vision-based navigation and guidance designs suggested in this paper are integrated with realtime image processing algorithm and the entire vision-based control system are evaluated in the closed-loop 6 DoF flight simulation.

Original languageEnglish (US)
Title of host publicationCollection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2007
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
Number of pages11
ISBN (Print)1563479044, 9781563479045
StatePublished - 2007
EventAIAA Guidance, Navigation, and Control Conference 2007 - Hilton Head, SC, United States
Duration: Aug 20 2007Aug 23 2007

Publication series

NameCollection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2007


OtherAIAA Guidance, Navigation, and Control Conference 2007
Country/TerritoryUnited States
CityHilton Head, SC

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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