Location
Room # EB204
Start Date
5-6-2019 9:30 AM
Description
This paper first summarizes recent results of a proposed method for multiple, small, fixed-wing aircraft cooperatively localizing in GPS-denied environments. It then provides a significant future works discussion to provide a vision for the future of cooperative navigation. The goal of this work is to show that many, small, potentially-lower-cost vehicles could collaboratively localize better than a single, more-accurate, higher-cost GPS-denied system. This work is guided by a novel methodology called relative navigation, which has been developed in prior work. Initial work focused on the development and testing of a monocular, visual-inertial odometry for fixed-wing aircraft that accounts for fixed-wing flight characteristics and sensing requirements. The front-end publishes information that enables a back-end where the odometry from multiple vehicles is combined with inter-vehicle measurements and is communicated and shared between vehicles. Each vehicle is able to create a global, backend, graph-based map and optimize it as new information is gained and measurements between vehicles overconstrain the graph. These inter-vehicle measurements allow the optimization to remove accumulated drift for more accurate estimates.
Progress on GPS-Denied, Multi-Vehicle, Fixed-Wing Cooperative Localization
Room # EB204
This paper first summarizes recent results of a proposed method for multiple, small, fixed-wing aircraft cooperatively localizing in GPS-denied environments. It then provides a significant future works discussion to provide a vision for the future of cooperative navigation. The goal of this work is to show that many, small, potentially-lower-cost vehicles could collaboratively localize better than a single, more-accurate, higher-cost GPS-denied system. This work is guided by a novel methodology called relative navigation, which has been developed in prior work. Initial work focused on the development and testing of a monocular, visual-inertial odometry for fixed-wing aircraft that accounts for fixed-wing flight characteristics and sensing requirements. The front-end publishes information that enables a back-end where the odometry from multiple vehicles is combined with inter-vehicle measurements and is communicated and shared between vehicles. Each vehicle is able to create a global, backend, graph-based map and optimize it as new information is gained and measurements between vehicles overconstrain the graph. These inter-vehicle measurements allow the optimization to remove accumulated drift for more accurate estimates.
Comments
Session 3