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Paper TuA01.1

Bry, Adam (Massachusetts Institute of Technology), Bachrach, Abraham (Massachusetts Institute of Technology,), Roy, Nicholas (Massachusetts Institute of Technology)

State Estimation for Aggressive Flight in GPS-Denied Environments Using Onboard Sensing

Scheduled for presentation during the Regular Session "Estimation and Control for UAVs" (TuA01), Tuesday, May 15, 2012, 08:30−08:45, Meeting Room 1 (Mini-sota)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on June 22, 2018

Keywords Aerial Robotics, Localization, Sensor Fusion

Abstract

In this paper we present a state estimation method based on an inertial measurement unit (IMU) and a planar laser range finder suitable for use in real-time on a fixed-wing micro air vehicle (MAV). The algorithm is capable of maintaing accurate state estimates during aggressive flight in unstructured 3D environments without the use of an external positioning system. Our localization algorithm is based on an extension of the Gaussian Particle Filter. We partition the state according to measurement independence relationships and then calculate a pseudo-linear update which allows us to use 20x fewer particles than a naive implementation to achieve similar accuracy in the state estimate. We also propose a multi-step forward fitting method to identify the noise parameters of the IMU and compare results with and without accurate position measurements. Our process and measurement models integrate naturally with an exponential coordinates representation of the attitude uncertainty. We demonstrate our algorithms experimentally on a fixed-wing vehicle flying in a challenging indoor environment.

 

 

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